Overview

Dataset statistics

Number of variables201
Number of observations7467
Missing cells796
Missing cells (%)0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory79.6 MiB
Average record size in memory10.9 KiB

Variable types

Categorical192
Numeric9

Alerts

Año has constant value "2010" Constant
entidad has constant value "26" Constant
nom_ent has constant value "Sonora" Constant
nom_mun has a high cardinality: 73 distinct values High cardinality
nom_loc has a high cardinality: 5549 distinct values High cardinality
pobmas has a high cardinality: 532 distinct values High cardinality
pobfem has a high cardinality: 515 distinct values High cardinality
p_0a2 has a high cardinality: 203 distinct values High cardinality
p_0a2_m has a high cardinality: 160 distinct values High cardinality
p_0a2_f has a high cardinality: 160 distinct values High cardinality
p_3ymas has a high cardinality: 665 distinct values High cardinality
p_3ymas_m has a high cardinality: 535 distinct values High cardinality
p_3ymas_f has a high cardinality: 508 distinct values High cardinality
p_5ymas has a high cardinality: 659 distinct values High cardinality
p_5ymas_m has a high cardinality: 515 distinct values High cardinality
p_5ymas_f has a high cardinality: 502 distinct values High cardinality
p_12ymas has a high cardinality: 620 distinct values High cardinality
p_12ymas_m has a high cardinality: 488 distinct values High cardinality
p_12ymas_f has a high cardinality: 463 distinct values High cardinality
p_15ymas has a high cardinality: 612 distinct values High cardinality
p_15ymas_m has a high cardinality: 477 distinct values High cardinality
p_15ymas_f has a high cardinality: 448 distinct values High cardinality
p_18ymas has a high cardinality: 590 distinct values High cardinality
p_18ymas_m has a high cardinality: 451 distinct values High cardinality
p_18ymas_f has a high cardinality: 437 distinct values High cardinality
p_3a5 has a high cardinality: 211 distinct values High cardinality
p_3a5_m has a high cardinality: 166 distinct values High cardinality
p_3a5_f has a high cardinality: 162 distinct values High cardinality
p_6a11 has a high cardinality: 291 distinct values High cardinality
p_6a11_m has a high cardinality: 223 distinct values High cardinality
p_6a11_f has a high cardinality: 215 distinct values High cardinality
p_8a14 has a high cardinality: 304 distinct values High cardinality
p_8a14_m has a high cardinality: 231 distinct values High cardinality
p_8a14_f has a high cardinality: 226 distinct values High cardinality
p_12a14 has a high cardinality: 211 distinct values High cardinality
p_12a14_m has a high cardinality: 160 distinct values High cardinality
p_12a14_f has a high cardinality: 167 distinct values High cardinality
p_15a17 has a high cardinality: 217 distinct values High cardinality
p_15a17_m has a high cardinality: 166 distinct values High cardinality
p_15a17_f has a high cardinality: 154 distinct values High cardinality
p_18a24 has a high cardinality: 283 distinct values High cardinality
p_18a24_m has a high cardinality: 222 distinct values High cardinality
p_18a24_f has a high cardinality: 210 distinct values High cardinality
p_15a49_f has a high cardinality: 398 distinct values High cardinality
p_60ymas has a high cardinality: 295 distinct values High cardinality
p_60ymas_m has a high cardinality: 228 distinct values High cardinality
p_60ymas_f has a high cardinality: 217 distinct values High cardinality
rel_h_m has a high cardinality: 934 distinct values High cardinality
pob0_14 has a high cardinality: 418 distinct values High cardinality
pob15_64 has a high cardinality: 564 distinct values High cardinality
pob65_mas has a high cardinality: 260 distinct values High cardinality
prom_hnv has a high cardinality: 320 distinct values High cardinality
pnacent has a high cardinality: 661 distinct values High cardinality
pnacent_m has a high cardinality: 502 distinct values High cardinality
pnacent_f has a high cardinality: 486 distinct values High cardinality
pnacoe has a high cardinality: 268 distinct values High cardinality
pnacoe_m has a high cardinality: 219 distinct values High cardinality
pnacoe_f has a high cardinality: 195 distinct values High cardinality
pres2005 has a high cardinality: 638 distinct values High cardinality
pres2005_m has a high cardinality: 503 distinct values High cardinality
pres2005_f has a high cardinality: 487 distinct values High cardinality
presoe05 has a high cardinality: 147 distinct values High cardinality
presoe05_m has a high cardinality: 128 distinct values High cardinality
presoe05_f has a high cardinality: 108 distinct values High cardinality
p3ym_hli has a high cardinality: 217 distinct values High cardinality
p3ym_hli_m has a high cardinality: 175 distinct values High cardinality
p3ym_hli_f has a high cardinality: 152 distinct values High cardinality
p3hli_he has a high cardinality: 220 distinct values High cardinality
p3hli_he_m has a high cardinality: 171 distinct values High cardinality
p3hli_he_f has a high cardinality: 150 distinct values High cardinality
p5_hli has a high cardinality: 223 distinct values High cardinality
p5_hli_he has a high cardinality: 213 distinct values High cardinality
phog_ind has a high cardinality: 293 distinct values High cardinality
pcon_lim has a high cardinality: 218 distinct values High cardinality
pclim_mot has a high cardinality: 170 distinct values High cardinality
pclim_vis has a high cardinality: 135 distinct values High cardinality
pclim_leng has a high cardinality: 78 distinct values High cardinality
pclim_aud has a high cardinality: 87 distinct values High cardinality
pclim_mot2 has a high cardinality: 74 distinct values High cardinality
pclim_men has a high cardinality: 69 distinct values High cardinality
pclim_men2 has a high cardinality: 89 distinct values High cardinality
psin_lim has a high cardinality: 688 distinct values High cardinality
p3a5_noa has a high cardinality: 164 distinct values High cardinality
p3a5_noa_m has a high cardinality: 136 distinct values High cardinality
p3a5_noa_f has a high cardinality: 131 distinct values High cardinality
p6a11_noa has a high cardinality: 70 distinct values High cardinality
p6a11_noam has a high cardinality: 60 distinct values High cardinality
p6a11_noaf has a high cardinality: 58 distinct values High cardinality
p12a14noa has a high cardinality: 79 distinct values High cardinality
p12a14noam has a high cardinality: 65 distinct values High cardinality
p12a14noaf has a high cardinality: 58 distinct values High cardinality
p15a17a has a high cardinality: 184 distinct values High cardinality
p15a17a_m has a high cardinality: 144 distinct values High cardinality
p15a17a_f has a high cardinality: 139 distinct values High cardinality
p18a24a has a high cardinality: 162 distinct values High cardinality
p18a24a_m has a high cardinality: 126 distinct values High cardinality
p18a24a_f has a high cardinality: 122 distinct values High cardinality
p8a14an has a high cardinality: 82 distinct values High cardinality
p8a14an_m has a high cardinality: 62 distinct values High cardinality
p8a14an_f has a high cardinality: 56 distinct values High cardinality
p15ym_an has a high cardinality: 182 distinct values High cardinality
p15ym_an_m has a high cardinality: 137 distinct values High cardinality
p15ym_an_f has a high cardinality: 133 distinct values High cardinality
p15ym_se has a high cardinality: 192 distinct values High cardinality
p15ym_se_m has a high cardinality: 143 distinct values High cardinality
p15ym_se_f has a high cardinality: 138 distinct values High cardinality
p15pri_in has a high cardinality: 309 distinct values High cardinality
p15pri_inm has a high cardinality: 238 distinct values High cardinality
p15pri_inf has a high cardinality: 219 distinct values High cardinality
p15pri_co has a high cardinality: 292 distinct values High cardinality
p15pri_com has a high cardinality: 232 distinct values High cardinality
p15pri_cof has a high cardinality: 219 distinct values High cardinality
p15sec_in has a high cardinality: 202 distinct values High cardinality
p15sec_inm has a high cardinality: 163 distinct values High cardinality
p15sec_inf has a high cardinality: 143 distinct values High cardinality
p15sec_co has a high cardinality: 350 distinct values High cardinality
p15sec_com has a high cardinality: 269 distinct values High cardinality
p15sec_cof has a high cardinality: 268 distinct values High cardinality
p18ym_pb has a high cardinality: 309 distinct values High cardinality
p18ym_pb_m has a high cardinality: 236 distinct values High cardinality
p18ym_pb_f has a high cardinality: 226 distinct values High cardinality
graproes has a high cardinality: 634 distinct values High cardinality
graproes_m has a high cardinality: 599 distinct values High cardinality
graproes_f has a high cardinality: 577 distinct values High cardinality
pea has a high cardinality: 464 distinct values High cardinality
pea_m has a high cardinality: 425 distinct values High cardinality
pea_f has a high cardinality: 256 distinct values High cardinality
pe_inac has a high cardinality: 481 distinct values High cardinality
pe_inac_m has a high cardinality: 288 distinct values High cardinality
pe_inac_f has a high cardinality: 415 distinct values High cardinality
pocupada has a high cardinality: 470 distinct values High cardinality
pocupada_m has a high cardinality: 406 distinct values High cardinality
pocupada_f has a high cardinality: 257 distinct values High cardinality
pdesocup has a high cardinality: 151 distinct values High cardinality
pdesocup_m has a high cardinality: 142 distinct values High cardinality
pdesocup_f has a high cardinality: 73 distinct values High cardinality
psinder has a high cardinality: 401 distinct values High cardinality
pder_ss has a high cardinality: 613 distinct values High cardinality
pder_imss has a high cardinality: 375 distinct values High cardinality
pder_iste has a high cardinality: 176 distinct values High cardinality
pder_istee has a high cardinality: 189 distinct values High cardinality
pder_segp has a high cardinality: 485 distinct values High cardinality
p12ym_solt has a high cardinality: 397 distinct values High cardinality
p12ym_casa has a high cardinality: 505 distinct values High cardinality
p12ym_sepa has a high cardinality: 244 distinct values High cardinality
pcatolica has a high cardinality: 641 distinct values High cardinality
pncatolica has a high cardinality: 247 distinct values High cardinality
psin_relig has a high cardinality: 233 distinct values High cardinality
tothog has a high cardinality: 401 distinct values High cardinality
hogjef_m has a high cardinality: 372 distinct values High cardinality
hogjef_f has a high cardinality: 211 distinct values High cardinality
pobhog has a high cardinality: 688 distinct values High cardinality
phogjef_m has a high cardinality: 637 distinct values High cardinality
phogjef_f has a high cardinality: 345 distinct values High cardinality
tvivpar has a high cardinality: 446 distinct values High cardinality
vivpar_hab has a high cardinality: 401 distinct values High cardinality
tvivparhab has a high cardinality: 406 distinct values High cardinality
vivpar_des has a high cardinality: 195 distinct values High cardinality
vivpar_ut has a high cardinality: 190 distinct values High cardinality
ocupvivpar has a high cardinality: 688 distinct values High cardinality
prom_ocup has a high cardinality: 323 distinct values High cardinality
pro_ocup_c has a high cardinality: 262 distinct values High cardinality
vph_pisodt has a high cardinality: 394 distinct values High cardinality
vph_pisoti has a high cardinality: 139 distinct values High cardinality
vph_1dor has a high cardinality: 260 distinct values High cardinality
vph_2ymasd has a high cardinality: 321 distinct values High cardinality
vph_1cuart has a high cardinality: 149 distinct values High cardinality
vph_2cuart has a high cardinality: 204 distinct values High cardinality
vph_3ymasc has a high cardinality: 348 distinct values High cardinality
vph_c_elec has a high cardinality: 397 distinct values High cardinality
vph_s_elec has a high cardinality: 108 distinct values High cardinality
vph_aguadv has a high cardinality: 379 distinct values High cardinality
vph_aguafv has a high cardinality: 142 distinct values High cardinality
vph_excsa has a high cardinality: 393 distinct values High cardinality
vph_drenaj has a high cardinality: 331 distinct values High cardinality
vph_nodren has a high cardinality: 235 distinct values High cardinality
vph_c_serv has a high cardinality: 320 distinct values High cardinality
vph_snbien has a high cardinality: 78 distinct values High cardinality
vph_radio has a high cardinality: 329 distinct values High cardinality
vph_tv has a high cardinality: 383 distinct values High cardinality
vph_refri has a high cardinality: 376 distinct values High cardinality
vph_lavad has a high cardinality: 312 distinct values High cardinality
vph_autom has a high cardinality: 295 distinct values High cardinality
vph_pc has a high cardinality: 185 distinct values High cardinality
vph_telef has a high cardinality: 214 distinct values High cardinality
vph_cel has a high cardinality: 328 distinct values High cardinality
vph_inter has a high cardinality: 143 distinct values High cardinality
longitud is highly correlated with latitudHigh correlation
latitud is highly correlated with longitud and 1 other fieldsHigh correlation
altitud is highly correlated with latitudHigh correlation
pobtot is highly correlated with vivtot and 1 other fieldsHigh correlation
vivtot is highly correlated with pobtot and 1 other fieldsHigh correlation
tvivhab is highly correlated with pobtot and 1 other fieldsHigh correlation
longitud is highly correlated with latitudHigh correlation
latitud is highly correlated with longitudHigh correlation
pobtot is highly correlated with vivtot and 1 other fieldsHigh correlation
vivtot is highly correlated with pobtot and 1 other fieldsHigh correlation
tvivhab is highly correlated with pobtot and 1 other fieldsHigh correlation
longitud is highly correlated with latitudHigh correlation
latitud is highly correlated with longitudHigh correlation
pobtot is highly correlated with vivtot and 1 other fieldsHigh correlation
vivtot is highly correlated with pobtot and 1 other fieldsHigh correlation
tvivhab is highly correlated with pobtot and 1 other fieldsHigh correlation
p6a11_noaf is highly correlated with pclim_men and 22 other fieldsHigh correlation
pclim_men is highly correlated with p6a11_noaf and 22 other fieldsHigh correlation
nom_mun is highly correlated with Año and 2 other fieldsHigh correlation
Año is highly correlated with p6a11_noaf and 23 other fieldsHigh correlation
p12a14noa is highly correlated with p6a11_noaf and 22 other fieldsHigh correlation
p3hlinhe is highly correlated with p6a11_noaf and 22 other fieldsHigh correlation
pclim_mot2 is highly correlated with p6a11_noaf and 22 other fieldsHigh correlation
pclim_aud is highly correlated with p6a11_noaf and 22 other fieldsHigh correlation
pclim_men2 is highly correlated with p6a11_noaf and 22 other fieldsHigh correlation
vph_snbien is highly correlated with p6a11_noaf and 22 other fieldsHigh correlation
p6a11_noa is highly correlated with p6a11_noaf and 22 other fieldsHigh correlation
p12a14noam is highly correlated with p6a11_noaf and 22 other fieldsHigh correlation
p6a11_noam is highly correlated with p6a11_noaf and 22 other fieldsHigh correlation
pclim_leng is highly correlated with p6a11_noaf and 22 other fieldsHigh correlation
pdesocup_f is highly correlated with p6a11_noaf and 22 other fieldsHigh correlation
entidad is highly correlated with p6a11_noaf and 23 other fieldsHigh correlation
p8a14an is highly correlated with p6a11_noaf and 22 other fieldsHigh correlation
nom_ent is highly correlated with p6a11_noaf and 23 other fieldsHigh correlation
p3hlinhe_f is highly correlated with p6a11_noaf and 22 other fieldsHigh correlation
p8a14an_m is highly correlated with p6a11_noaf and 22 other fieldsHigh correlation
p5_hli_nhe is highly correlated with p6a11_noaf and 22 other fieldsHigh correlation
potras_rel is highly correlated with p6a11_noaf and 22 other fieldsHigh correlation
p12a14noaf is highly correlated with p6a11_noaf and 22 other fieldsHigh correlation
p3hlinhe_m is highly correlated with p6a11_noaf and 22 other fieldsHigh correlation
p8a14an_f is highly correlated with p6a11_noaf and 22 other fieldsHigh correlation
mun is highly correlated with nom_mun and 4 other fieldsHigh correlation
nom_mun is highly correlated with mun and 28 other fieldsHigh correlation
loc is highly correlated with mun and 2 other fieldsHigh correlation
longitud is highly correlated with mun and 3 other fieldsHigh correlation
latitud is highly correlated with mun and 4 other fieldsHigh correlation
altitud is highly correlated with mun and 3 other fieldsHigh correlation
pobtot is highly correlated with nom_mun and 24 other fieldsHigh correlation
p3hlinhe is highly correlated with nom_mun and 24 other fieldsHigh correlation
p3hlinhe_m is highly correlated with nom_mun and 24 other fieldsHigh correlation
p3hlinhe_f is highly correlated with nom_mun and 24 other fieldsHigh correlation
p5_hli_nhe is highly correlated with nom_mun and 24 other fieldsHigh correlation
pclim_leng is highly correlated with nom_mun and 24 other fieldsHigh correlation
pclim_aud is highly correlated with nom_mun and 24 other fieldsHigh correlation
pclim_mot2 is highly correlated with nom_mun and 24 other fieldsHigh correlation
pclim_men is highly correlated with nom_mun and 24 other fieldsHigh correlation
pclim_men2 is highly correlated with nom_mun and 24 other fieldsHigh correlation
p6a11_noa is highly correlated with nom_mun and 24 other fieldsHigh correlation
p6a11_noam is highly correlated with nom_mun and 24 other fieldsHigh correlation
p6a11_noaf is highly correlated with nom_mun and 24 other fieldsHigh correlation
p12a14noa is highly correlated with nom_mun and 24 other fieldsHigh correlation
p12a14noam is highly correlated with nom_mun and 24 other fieldsHigh correlation
p12a14noaf is highly correlated with nom_mun and 24 other fieldsHigh correlation
p8a14an is highly correlated with nom_mun and 24 other fieldsHigh correlation
p8a14an_m is highly correlated with nom_mun and 24 other fieldsHigh correlation
p8a14an_f is highly correlated with nom_mun and 24 other fieldsHigh correlation
pdesocup_f is highly correlated with nom_mun and 24 other fieldsHigh correlation
potras_rel is highly correlated with nom_mun and 24 other fieldsHigh correlation
vivtot is highly correlated with nom_mun and 24 other fieldsHigh correlation
tvivhab is highly correlated with nom_mun and 24 other fieldsHigh correlation
vph_snbien is highly correlated with nom_mun and 24 other fieldsHigh correlation
tam_loc is highly correlated with pobtot and 23 other fieldsHigh correlation
longitud has 199 (2.7%) missing values Missing
latitud has 199 (2.7%) missing values Missing
altitud has 199 (2.7%) missing values Missing
tam_loc has 199 (2.7%) missing values Missing
pobtot is highly skewed (γ1 = 66.2972147) Skewed
vivtot is highly skewed (γ1 = 66.07889289) Skewed
tvivhab is highly skewed (γ1 = 65.82447851) Skewed

Reproduction

Analysis started2022-11-07 04:05:58.240684
Analysis finished2022-11-07 04:07:31.760933
Duration1 minute and 33.52 seconds
Software versionpandas-profiling v3.1.0
Download configurationconfig.json

Variables

Año
Categorical

CONSTANT
HIGH CORRELATION
REJECTED

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size444.9 KiB
2010
7467 

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2010
2nd row2010
3rd row2010
4th row2010
5th row2010

Common Values

ValueCountFrequency (%)
20107467
100.0%

Length

2022-11-06T21:07:31.904927image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-06T21:07:31.993926image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
ValueCountFrequency (%)
20107467
100.0%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

entidad
Categorical

CONSTANT
HIGH CORRELATION
REJECTED

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size430.4 KiB
26
7467 

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row26
2nd row26
3rd row26
4th row26
5th row26

Common Values

ValueCountFrequency (%)
267467
100.0%

Length

2022-11-06T21:07:34.049718image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-06T21:07:34.170760image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
ValueCountFrequency (%)
267467
100.0%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

nom_ent
Categorical

CONSTANT
HIGH CORRELATION
REJECTED

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size459.5 KiB
Sonora
7467 

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowSonora
2nd rowSonora
3rd rowSonora
4th rowSonora
5th rowSonora

Common Values

ValueCountFrequency (%)
Sonora7467
100.0%

Length

2022-11-06T21:07:34.309757image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-06T21:07:34.408756image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
ValueCountFrequency (%)
sonora7467
100.0%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

mun
Real number (ℝ≥0)

HIGH CORRELATION

Distinct73
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean32.05129235
Minimum0
Maximum72
Zeros3
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size58.5 KiB
2022-11-06T21:07:34.556762image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3
Q118
median30
Q345
95-th percentile69
Maximum72
Range72
Interquartile range (IQR)27

Descriptive statistics

Standard deviation18.59639188
Coefficient of variation (CV)0.5802072401
Kurtosis-0.6222884173
Mean32.05129235
Median Absolute Deviation (MAD)12
Skewness0.4435166595
Sum239327
Variance345.8257909
MonotonicityIncreasing
2022-11-06T21:07:35.027822image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
301005
 
13.5%
18985
 
13.2%
55374
 
5.0%
29359
 
4.8%
17344
 
4.6%
3320
 
4.3%
42303
 
4.1%
26216
 
2.9%
33213
 
2.9%
12197
 
2.6%
Other values (63)3151
42.2%
ValueCountFrequency (%)
03
 
< 0.1%
112
 
0.2%
2145
1.9%
3320
4.3%
4147
2.0%
55
 
0.1%
675
 
1.0%
79
 
0.1%
84
 
0.1%
920
 
0.3%
ValueCountFrequency (%)
72132
1.8%
7181
1.1%
7079
1.1%
69106
1.4%
6838
 
0.5%
678
 
0.1%
6670
0.9%
6572
1.0%
6445
 
0.6%
633
 
< 0.1%

nom_mun
Categorical

HIGH CARDINALITY
HIGH CORRELATION
HIGH CORRELATION

Distinct73
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size513.4 KiB
Hermosillo
1005 
Cajeme
985 
San Luis Río Colorado
 
374
Guaymas
 
359
Caborca
 
344
Other values (68)
4400 

Length

Max length29
Median length7
Mean length9.14102049
Min length4

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowTotal de la entidad Sonora
2nd rowTotal de la entidad Sonora
3rd rowTotal de la entidad Sonora
4th rowAconchi
5th rowAconchi

Common Values

ValueCountFrequency (%)
Hermosillo1005
 
13.5%
Cajeme985
 
13.2%
San Luis Río Colorado374
 
5.0%
Guaymas359
 
4.8%
Caborca344
 
4.6%
Alamos320
 
4.3%
Navojoa303
 
4.1%
Etchojoa216
 
2.9%
Huatabampo213
 
2.9%
Bácum197
 
2.6%
Other values (63)3151
42.2%

Length

2022-11-06T21:07:35.297855image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
hermosillo1005
 
9.8%
cajeme985
 
9.6%
san620
 
6.1%
río506
 
4.9%
luis374
 
3.7%
colorado374
 
3.7%
guaymas359
 
3.5%
caborca344
 
3.4%
alamos320
 
3.1%
navojoa303
 
3.0%
Other values (86)5043
49.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

loc
Real number (ℝ≥0)

HIGH CORRELATION

Distinct2386
Distinct (%)32.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean889.2391858
Minimum0
Maximum9999
Zeros73
Zeros (%)1.0%
Negative0
Negative (%)0.0%
Memory size58.5 KiB
2022-11-06T21:07:35.518856image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile11
Q1114
median343
Q3937.5
95-th percentile3269.7
Maximum9999
Range9999
Interquartile range (IQR)823.5

Descriptive statistics

Standard deviation1517.370189
Coefficient of variation (CV)1.70636901
Kurtosis19.55339996
Mean889.2391858
Median Absolute Deviation (MAD)284
Skewness3.950933978
Sum6639949
Variance2302412.289
MonotonicityNot monotonic
2022-11-06T21:07:35.808856image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
073
 
1.0%
172
 
1.0%
999869
 
0.9%
999957
 
0.8%
233
 
0.4%
829
 
0.4%
726
 
0.3%
926
 
0.3%
2525
 
0.3%
1124
 
0.3%
Other values (2376)7033
94.2%
ValueCountFrequency (%)
073
1.0%
172
1.0%
233
0.4%
321
 
0.3%
419
 
0.3%
518
 
0.2%
622
 
0.3%
726
 
0.3%
829
 
0.4%
926
 
0.3%
ValueCountFrequency (%)
999957
0.8%
999869
0.9%
39631
 
< 0.1%
39611
 
< 0.1%
39591
 
< 0.1%
39541
 
< 0.1%
39521
 
< 0.1%
39511
 
< 0.1%
39501
 
< 0.1%
39471
 
< 0.1%

nom_loc
Categorical

HIGH CARDINALITY

Distinct5549
Distinct (%)74.3%
Missing0
Missing (%)0.0%
Memory size572.3 KiB
Ninguno
 
115
Total del Municipio
 
72
Localidades de una vivienda
 
69
Localidades de dos viviendas
 
57
San Francisco
 
30
Other values (5544)
7124 

Length

Max length56
Median length12
Mean length15.28297844
Min length2

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4946 ?
Unique (%)66.2%

Sample

1st rowTotal de la Entidad
2nd rowLocalidades de una vivienda
3rd rowLocalidades de dos viviendas
4th rowTotal del Municipio
5th rowAconchi

Common Values

ValueCountFrequency (%)
Ninguno115
 
1.5%
Total del Municipio72
 
1.0%
Localidades de una vivienda69
 
0.9%
Localidades de dos viviendas57
 
0.8%
San Francisco30
 
0.4%
El Ranchito29
 
0.4%
San Antonio29
 
0.4%
San Juan19
 
0.3%
San José19
 
0.3%
El Porvenir17
 
0.2%
Other values (5539)7011
93.9%

Length

2022-11-06T21:07:36.076853image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
el1506
 
8.0%
la1111
 
5.9%
de675
 
3.6%
san608
 
3.2%
los455
 
2.4%
las324
 
1.7%
santa290
 
1.5%
campo285
 
1.5%
del210
 
1.1%
rancho169
 
0.9%
Other values (4190)13171
70.0%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

longitud
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct5241
Distinct (%)72.1%
Missing199
Missing (%)2.7%
Infinite0
Infinite (%)0.0%
Mean1104508.459
Minimum1082903
Maximum1150126
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size58.5 KiB
2022-11-06T21:07:36.290854image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/

Quantile statistics

Minimum1082903
5-th percentile1085757.35
Q11094654.25
median1101944
Q31111463.25
95-th percentile1141813.25
Maximum1150126
Range67223
Interquartile range (IQR)16809

Descriptive statistics

Standard deviation13710.61104
Coefficient of variation (CV)0.01241331466
Kurtosis1.839389289
Mean1104508.459
Median Absolute Deviation (MAD)8195
Skewness1.302473653
Sum8027567477
Variance187980855.1
MonotonicityNot monotonic
2022-11-06T21:07:36.528851image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
109560016
 
0.2%
109533015
 
0.2%
110005610
 
0.1%
11003218
 
0.1%
10955598
 
0.1%
11054387
 
0.1%
11054307
 
0.1%
10951027
 
0.1%
10953257
 
0.1%
10951007
 
0.1%
Other values (5231)7176
96.1%
(Missing)199
 
2.7%
ValueCountFrequency (%)
10829031
< 0.1%
10830041
< 0.1%
10830301
< 0.1%
10830531
< 0.1%
10831011
< 0.1%
10831121
< 0.1%
10832201
< 0.1%
10833191
< 0.1%
10833231
< 0.1%
10833241
< 0.1%
ValueCountFrequency (%)
11501261
< 0.1%
11501252
< 0.1%
11500542
< 0.1%
11500531
< 0.1%
11500511
< 0.1%
11500421
< 0.1%
11500411
< 0.1%
11500201
< 0.1%
11500191
< 0.1%
11500181
< 0.1%

latitud
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct5525
Distinct (%)76.0%
Missing199
Missing (%)2.7%
Infinite0
Infinite (%)0.0%
Mean288084.2705
Minimum261926
Maximum322914
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size58.5 KiB
2022-11-06T21:07:36.830896image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/

Quantile statistics

Minimum261926
5-th percentile265307.75
Q1272940
median284856.5
Q3303601.75
95-th percentile318659.55
Maximum322914
Range60988
Interquartile range (IQR)30661.75

Descriptive statistics

Standard deviation16523.51983
Coefficient of variation (CV)0.05735654988
Kurtosis-1.045230444
Mean288084.2705
Median Absolute Deviation (MAD)12907.5
Skewness0.384787995
Sum2093796478
Variance273026707.6
MonotonicityNot monotonic
2022-11-06T21:07:37.072852image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
27190012
 
0.2%
27311010
 
0.1%
2724009
 
0.1%
2731158
 
0.1%
2720088
 
0.1%
2713308
 
0.1%
2721108
 
0.1%
2721178
 
0.1%
2714368
 
0.1%
2710157
 
0.1%
Other values (5515)7182
96.2%
(Missing)199
 
2.7%
ValueCountFrequency (%)
2619261
< 0.1%
2621591
< 0.1%
2622581
< 0.1%
2623191
< 0.1%
2624031
< 0.1%
2624181
< 0.1%
2624211
< 0.1%
2624231
< 0.1%
2624281
< 0.1%
2625251
< 0.1%
ValueCountFrequency (%)
3229141
< 0.1%
3229031
< 0.1%
3229011
< 0.1%
3228491
< 0.1%
3228441
< 0.1%
3228391
< 0.1%
3228362
< 0.1%
3228211
< 0.1%
3228201
< 0.1%
3228141
< 0.1%

altitud
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct1263
Distinct (%)17.4%
Missing199
Missing (%)2.7%
Infinite0
Infinite (%)0.0%
Mean351.4266648
Minimum0
Maximum2130
Zeros6
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size58.5 KiB
2022-11-06T21:07:37.290854image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile10
Q130
median147.5
Q3597
95-th percentile1257.65
Maximum2130
Range2130
Interquartile range (IQR)567

Descriptive statistics

Standard deviation422.2868476
Coefficient of variation (CV)1.20163576
Kurtosis0.773173397
Mean351.4266648
Median Absolute Deviation (MAD)131.5
Skewness1.293855286
Sum2554169
Variance178326.1816
MonotonicityNot monotonic
2022-11-06T21:07:37.500855image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10214
 
2.9%
30205
 
2.7%
20136
 
1.8%
40122
 
1.6%
27100
 
1.3%
1788
 
1.2%
987
 
1.2%
1985
 
1.1%
2981
 
1.1%
5080
 
1.1%
Other values (1253)6070
81.3%
(Missing)199
 
2.7%
ValueCountFrequency (%)
06
 
0.1%
116
 
0.2%
220
 
0.3%
317
 
0.2%
433
 
0.4%
533
 
0.4%
617
 
0.2%
730
 
0.4%
826
 
0.3%
987
1.2%
ValueCountFrequency (%)
21301
< 0.1%
21201
< 0.1%
21031
< 0.1%
21001
< 0.1%
20791
< 0.1%
20541
< 0.1%
20271
< 0.1%
19911
< 0.1%
19801
< 0.1%
19021
< 0.1%

pobtot
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
SKEWED

Distinct695
Distinct (%)9.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1075.489755
Minimum1
Maximum2662480
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size58.5 KiB
2022-11-06T21:07:37.723852image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median4
Q312
95-th percentile455.4
Maximum2662480
Range2662479
Interquartile range (IQR)10

Descriptive statistics

Standard deviation34221.76776
Coefficient of variation (CV)31.81970595
Kurtosis4966.771469
Mean1075.489755
Median Absolute Deviation (MAD)3
Skewness66.2972147
Sum8030682
Variance1171129388
MonotonicityNot monotonic
2022-11-06T21:07:38.013852image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
11364
18.3%
21118
15.0%
3755
 
10.1%
4636
 
8.5%
5521
 
7.0%
6385
 
5.2%
7225
 
3.0%
8196
 
2.6%
9146
 
2.0%
10119
 
1.6%
Other values (685)2002
26.8%
ValueCountFrequency (%)
11364
18.3%
21118
15.0%
3755
10.1%
4636
8.5%
5521
 
7.0%
6385
 
5.2%
7225
 
3.0%
8196
 
2.6%
9146
 
2.0%
10119
 
1.6%
ValueCountFrequency (%)
26624801
< 0.1%
7843421
< 0.1%
7150611
< 0.1%
4093101
< 0.1%
2986251
< 0.1%
2202921
< 0.1%
2125331
< 0.1%
1783801
< 0.1%
1580891
< 0.1%
1577291
< 0.1%

pobmas
Categorical

HIGH CARDINALITY

Distinct532
Distinct (%)7.1%
Missing0
Missing (%)0.0%
Memory size425.4 KiB
*
5250 
5
 
116
6
 
110
7
 
96
4
 
83
Other values (527)
1812 

Length

Max length7
Median length1
Mean length1.320878532
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique303 ?
Unique (%)4.1%

Sample

1st row1339612
2nd row7517
3rd row6553
4th row1405
5th row933

Common Values

ValueCountFrequency (%)
*5250
70.3%
5116
 
1.6%
6110
 
1.5%
796
 
1.3%
483
 
1.1%
870
 
0.9%
369
 
0.9%
967
 
0.9%
1060
 
0.8%
1156
 
0.7%
Other values (522)1490
 
20.0%

Length

2022-11-06T21:07:38.425860image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
5116
 
1.6%
6110
 
1.5%
796
 
1.3%
483
 
1.1%
870
 
0.9%
369
 
0.9%
967
 
0.9%
1060
 
0.8%
1156
 
0.7%
Other values (522)1490
 
20.0%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

pobfem
Categorical

HIGH CARDINALITY

Distinct515
Distinct (%)6.9%
Missing0
Missing (%)0.0%
Memory size425.2 KiB
*
5250 
4
 
111
5
 
97
8
 
93
7
 
90
Other values (510)
1826 

Length

Max length7
Median length1
Mean length1.296370698
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique307 ?
Unique (%)4.1%

Sample

1st row1322868
2nd row5078
3rd row2473
4th row1232
5th row808

Common Values

ValueCountFrequency (%)
*5250
70.3%
4111
 
1.5%
597
 
1.3%
893
 
1.2%
790
 
1.2%
388
 
1.2%
681
 
1.1%
969
 
0.9%
266
 
0.9%
1254
 
0.7%
Other values (505)1468
 
19.7%

Length

2022-11-06T21:07:38.896853image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
4111
 
1.5%
597
 
1.3%
893
 
1.2%
790
 
1.2%
388
 
1.2%
681
 
1.1%
969
 
0.9%
266
 
0.9%
1254
 
0.7%
Other values (505)1468
 
19.7%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p_0a2
Categorical

HIGH CARDINALITY

Distinct203
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size423.9 KiB
*
5250 
0
 
516
1
 
337
2
 
231
3
 
127
Other values (198)
1006 

Length

Max length6
Median length1
Mean length1.112361055
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique117 ?
Unique (%)1.6%

Sample

1st row146530
2nd row529
3rd row304
4th row125
5th row68

Common Values

ValueCountFrequency (%)
*5250
70.3%
0516
 
6.9%
1337
 
4.5%
2231
 
3.1%
3127
 
1.7%
486
 
1.2%
569
 
0.9%
753
 
0.7%
647
 
0.6%
843
 
0.6%
Other values (193)708
 
9.5%

Length

2022-11-06T21:07:39.152876image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
0516
 
6.9%
1337
 
4.5%
2231
 
3.1%
3127
 
1.7%
486
 
1.2%
569
 
0.9%
753
 
0.7%
647
 
0.6%
843
 
0.6%
Other values (193)708
 
9.5%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p_0a2_m
Categorical

HIGH CARDINALITY

Distinct160
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size423.6 KiB
*
5250 
0
745 
1
 
387
2
 
194
3
 
112
Other values (155)
779 

Length

Max length5
Median length1
Mean length1.076871568
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique98 ?
Unique (%)1.3%

Sample

1st row74572
2nd row271
3rd row155
4th row68
5th row37

Common Values

ValueCountFrequency (%)
*5250
70.3%
0745
 
10.0%
1387
 
5.2%
2194
 
2.6%
3112
 
1.5%
486
 
1.2%
571
 
1.0%
656
 
0.7%
752
 
0.7%
1036
 
0.5%
Other values (150)478
 
6.4%

Length

2022-11-06T21:07:39.353876image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
0745
 
10.0%
1387
 
5.2%
2194
 
2.6%
3112
 
1.5%
486
 
1.2%
571
 
1.0%
656
 
0.7%
752
 
0.7%
1036
 
0.5%
Other values (150)478
 
6.4%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p_0a2_f
Categorical

HIGH CARDINALITY

Distinct160
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size423.6 KiB
*
5250 
0
792 
1
 
365
2
 
185
3
 
106
Other values (155)
769 

Length

Max length5
Median length1
Mean length1.074327039
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique100 ?
Unique (%)1.3%

Sample

1st row71958
2nd row258
3rd row149
4th row57
5th row31

Common Values

ValueCountFrequency (%)
*5250
70.3%
0792
 
10.6%
1365
 
4.9%
2185
 
2.5%
3106
 
1.4%
487
 
1.2%
570
 
0.9%
657
 
0.8%
842
 
0.6%
738
 
0.5%
Other values (150)475
 
6.4%

Length

2022-11-06T21:07:39.568876image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
0792
 
10.6%
1365
 
4.9%
2185
 
2.5%
3106
 
1.4%
487
 
1.2%
570
 
0.9%
657
 
0.8%
842
 
0.6%
738
 
0.5%
Other values (150)475
 
6.4%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p_3ymas
Categorical

HIGH CARDINALITY

Distinct665
Distinct (%)8.9%
Missing0
Missing (%)0.0%
Memory size426.0 KiB
*
5250 
9
 
66
8
 
66
11
 
62
10
 
60
Other values (660)
1963 

Length

Max length7
Median length1
Mean length1.405383688
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique413 ?
Unique (%)5.5%

Sample

1st row2495659
2nd row11978
3rd row8676
4th row2508
5th row1669

Common Values

ValueCountFrequency (%)
*5250
70.3%
966
 
0.9%
866
 
0.9%
1162
 
0.8%
1060
 
0.8%
759
 
0.8%
1355
 
0.7%
1247
 
0.6%
1643
 
0.6%
1442
 
0.6%
Other values (655)1717
 
23.0%

Length

2022-11-06T21:07:39.784878image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
966
 
0.9%
866
 
0.9%
1162
 
0.8%
1060
 
0.8%
759
 
0.8%
1355
 
0.7%
1247
 
0.6%
1643
 
0.6%
1442
 
0.6%
Other values (655)1717
 
23.0%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p_3ymas_m
Categorical

HIGH CARDINALITY

Distinct535
Distinct (%)7.2%
Missing0
Missing (%)0.0%
Memory size425.3 KiB
*
5250 
5
 
118
6
 
114
4
 
104
7
 
84
Other values (530)
1797 

Length

Max length7
Median length1
Mean length1.311102183
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique331 ?
Unique (%)4.4%

Sample

1st row1254876
2nd row7206
3rd row6376
4th row1333
5th row892

Common Values

ValueCountFrequency (%)
*5250
70.3%
5118
 
1.6%
6114
 
1.5%
4104
 
1.4%
784
 
1.1%
382
 
1.1%
875
 
1.0%
968
 
0.9%
1059
 
0.8%
1250
 
0.7%
Other values (525)1463
 
19.6%

Length

2022-11-06T21:07:40.005876image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
5118
 
1.6%
6114
 
1.5%
4104
 
1.4%
784
 
1.1%
382
 
1.1%
875
 
1.0%
968
 
0.9%
1059
 
0.8%
1250
 
0.7%
Other values (525)1463
 
19.6%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p_3ymas_f
Categorical

HIGH CARDINALITY

Distinct508
Distinct (%)6.8%
Missing0
Missing (%)0.0%
Memory size425.2 KiB
*
5250 
5
 
115
4
 
109
3
 
101
8
 
99
Other values (503)
1793 

Length

Max length7
Median length1
Mean length1.2892728
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique302 ?
Unique (%)4.0%

Sample

1st row1240783
2nd row4772
3rd row2300
4th row1175
5th row777

Common Values

ValueCountFrequency (%)
*5250
70.3%
5115
 
1.5%
4109
 
1.5%
3101
 
1.4%
899
 
1.3%
786
 
1.2%
680
 
1.1%
275
 
1.0%
966
 
0.9%
1152
 
0.7%
Other values (498)1434
 
19.2%

Length

2022-11-06T21:07:40.201874image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
5115
 
1.5%
4109
 
1.5%
3101
 
1.4%
899
 
1.3%
786
 
1.2%
680
 
1.1%
275
 
1.0%
966
 
0.9%
1152
 
0.7%
Other values (498)1434
 
19.2%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p_5ymas
Categorical

HIGH CARDINALITY

Distinct659
Distinct (%)8.8%
Missing0
Missing (%)0.0%
Memory size426.0 KiB
*
5250 
8
 
78
10
 
76
7
 
60
9
 
60
Other values (654)
1943 

Length

Max length7
Median length1
Mean length1.399625017
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique400 ?
Unique (%)5.4%

Sample

1st row2391220
2nd row11578
3rd row8466
4th row2420
5th row1614

Common Values

ValueCountFrequency (%)
*5250
70.3%
878
 
1.0%
1076
 
1.0%
760
 
0.8%
960
 
0.8%
1255
 
0.7%
1149
 
0.7%
1348
 
0.6%
648
 
0.6%
1446
 
0.6%
Other values (649)1697
 
22.7%

Length

2022-11-06T21:07:40.411877image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
878
 
1.0%
1076
 
1.0%
760
 
0.8%
960
 
0.8%
1255
 
0.7%
1149
 
0.7%
1348
 
0.6%
648
 
0.6%
1446
 
0.6%
Other values (649)1697
 
22.7%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p_5ymas_m
Categorical

HIGH CARDINALITY

Distinct515
Distinct (%)6.9%
Missing0
Missing (%)0.0%
Memory size425.3 KiB
*
5250 
5
 
123
4
 
114
6
 
112
3
 
90
Other values (510)
1778 

Length

Max length7
Median length1
Mean length1.30628097
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique302 ?
Unique (%)4.0%

Sample

1st row1201533
2nd row7018
3rd row6269
4th row1282
5th row861

Common Values

ValueCountFrequency (%)
*5250
70.3%
5123
 
1.6%
4114
 
1.5%
6112
 
1.5%
390
 
1.2%
784
 
1.1%
879
 
1.1%
966
 
0.9%
1057
 
0.8%
1152
 
0.7%
Other values (505)1440
 
19.3%

Length

2022-11-06T21:07:40.602876image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
5123
 
1.6%
4114
 
1.5%
6112
 
1.5%
390
 
1.2%
784
 
1.1%
879
 
1.1%
966
 
0.9%
1057
 
0.8%
1152
 
0.7%
Other values (505)1440
 
19.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p_5ymas_f
Categorical

HIGH CARDINALITY

Distinct502
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size425.1 KiB
*
5250 
4
 
122
5
 
117
3
 
104
6
 
90
Other values (497)
1784 

Length

Max length7
Median length1
Mean length1.283112361
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique307 ?
Unique (%)4.1%

Sample

1st row1189687
2nd row4560
3rd row2197
4th row1138
5th row753

Common Values

ValueCountFrequency (%)
*5250
70.3%
4122
 
1.6%
5117
 
1.6%
3104
 
1.4%
690
 
1.2%
888
 
1.2%
784
 
1.1%
282
 
1.1%
964
 
0.9%
1156
 
0.7%
Other values (492)1410
 
18.9%

Length

2022-11-06T21:07:40.829877image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
4122
 
1.6%
5117
 
1.6%
3104
 
1.4%
690
 
1.2%
888
 
1.2%
784
 
1.1%
282
 
1.1%
964
 
0.9%
1156
 
0.7%
Other values (492)1410
 
18.9%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p_12ymas
Categorical

HIGH CARDINALITY

Distinct620
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Memory size425.8 KiB
*
5250 
8
 
88
7
 
85
9
 
78
10
 
69
Other values (615)
1897 

Length

Max length7
Median length1
Mean length1.374581492
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique381 ?
Unique (%)5.1%

Sample

1st row2025823
2nd row10341
3rd row7847
4th row2058
5th row1370

Common Values

ValueCountFrequency (%)
*5250
70.3%
888
 
1.2%
785
 
1.1%
978
 
1.0%
1069
 
0.9%
667
 
0.9%
1261
 
0.8%
1153
 
0.7%
552
 
0.7%
1348
 
0.6%
Other values (610)1616
 
21.6%

Length

2022-11-06T21:07:41.019882image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
888
 
1.2%
785
 
1.1%
978
 
1.0%
1069
 
0.9%
667
 
0.9%
1261
 
0.8%
1153
 
0.7%
552
 
0.7%
1348
 
0.6%
Other values (610)1616
 
21.6%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p_12ymas_m
Categorical

HIGH CARDINALITY

Distinct488
Distinct (%)6.5%
Missing0
Missing (%)0.0%
Memory size425.1 KiB
*
5250 
4
 
138
3
 
138
5
 
137
6
 
119
Other values (483)
1685 

Length

Max length7
Median length1
Mean length1.285790813
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique282 ?
Unique (%)3.8%

Sample

1st row1014961
2nd row6366
3rd row5926
4th row1085
5th row738

Common Values

ValueCountFrequency (%)
*5250
70.3%
4138
 
1.8%
3138
 
1.8%
5137
 
1.8%
6119
 
1.6%
784
 
1.1%
971
 
1.0%
869
 
0.9%
1054
 
0.7%
1145
 
0.6%
Other values (478)1362
 
18.2%

Length

2022-11-06T21:07:41.188878image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
4138
 
1.8%
3138
 
1.8%
5137
 
1.8%
6119
 
1.6%
784
 
1.1%
971
 
1.0%
869
 
0.9%
1054
 
0.7%
1145
 
0.6%
Other values (478)1362
 
18.2%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p_12ymas_f
Categorical

HIGH CARDINALITY

Distinct463
Distinct (%)6.2%
Missing0
Missing (%)0.0%
Memory size425.0 KiB
*
5250 
4
 
155
3
 
141
5
 
134
2
 
103
Other values (458)
1684 

Length

Max length7
Median length1
Mean length1.264363198
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique271 ?
Unique (%)3.6%

Sample

1st row1010862
2nd row3975
3rd row1921
4th row973
5th row632

Common Values

ValueCountFrequency (%)
*5250
70.3%
4155
 
2.1%
3141
 
1.9%
5134
 
1.8%
2103
 
1.4%
688
 
1.2%
784
 
1.1%
876
 
1.0%
163
 
0.8%
946
 
0.6%
Other values (453)1327
 
17.8%

Length

2022-11-06T21:07:41.405875image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
4155
 
2.1%
3141
 
1.9%
5134
 
1.8%
2103
 
1.4%
688
 
1.2%
784
 
1.1%
876
 
1.0%
163
 
0.8%
946
 
0.6%
Other values (453)1327
 
17.8%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p_15ymas
Categorical

HIGH CARDINALITY

Distinct612
Distinct (%)8.2%
Missing0
Missing (%)0.0%
Memory size425.7 KiB
*
5250 
8
 
100
7
 
95
6
 
79
10
 
72
Other values (607)
1871 

Length

Max length7
Median length1
Mean length1.362528459
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique379 ?
Unique (%)5.1%

Sample

1st row1874387
2nd row9792
3rd row7558
4th row1896
5th row1259

Common Values

ValueCountFrequency (%)
*5250
70.3%
8100
 
1.3%
795
 
1.3%
679
 
1.1%
1072
 
1.0%
971
 
1.0%
567
 
0.9%
1158
 
0.8%
1256
 
0.7%
1544
 
0.6%
Other values (602)1575
 
21.1%

Length

2022-11-06T21:07:41.630876image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
8100
 
1.3%
795
 
1.3%
679
 
1.1%
1072
 
1.0%
971
 
1.0%
567
 
0.9%
1158
 
0.8%
1256
 
0.7%
1544
 
0.6%
Other values (602)1575
 
21.1%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p_15ymas_m
Categorical

HIGH CARDINALITY

Distinct477
Distinct (%)6.4%
Missing0
Missing (%)0.0%
Memory size425.1 KiB
*
5250 
3
 
166
4
 
145
5
 
142
6
 
124
Other values (472)
1640 

Length

Max length6
Median length1
Mean length1.276282309
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique284 ?
Unique (%)3.8%

Sample

1st row937599
2nd row6074
3rd row5749
4th row993
5th row670

Common Values

ValueCountFrequency (%)
*5250
70.3%
3166
 
2.2%
4145
 
1.9%
5142
 
1.9%
6124
 
1.7%
970
 
0.9%
769
 
0.9%
865
 
0.9%
1048
 
0.6%
1143
 
0.6%
Other values (467)1345
 
18.0%

Length

2022-11-06T21:07:41.848879image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
3166
 
2.2%
4145
 
1.9%
5142
 
1.9%
6124
 
1.7%
970
 
0.9%
769
 
0.9%
865
 
0.9%
1048
 
0.6%
1143
 
0.6%
Other values (467)1345
 
18.0%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p_15ymas_f
Categorical

HIGH CARDINALITY

Distinct448
Distinct (%)6.0%
Missing0
Missing (%)0.0%
Memory size424.9 KiB
*
5250 
3
 
168
4
 
165
5
 
125
2
 
112
Other values (443)
1647 

Length

Max length6
Median length1
Mean length1.255524307
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique267 ?
Unique (%)3.6%

Sample

1st row936788
2nd row3718
3rd row1809
4th row903
5th row589

Common Values

ValueCountFrequency (%)
*5250
70.3%
3168
 
2.2%
4165
 
2.2%
5125
 
1.7%
2112
 
1.5%
692
 
1.2%
780
 
1.1%
167
 
0.9%
865
 
0.9%
944
 
0.6%
Other values (438)1299
 
17.4%

Length

2022-11-06T21:07:42.046875image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
3168
 
2.2%
4165
 
2.2%
5125
 
1.7%
2112
 
1.5%
692
 
1.2%
780
 
1.1%
167
 
0.9%
865
 
0.9%
944
 
0.6%
Other values (438)1299
 
17.4%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p_18ymas
Categorical

HIGH CARDINALITY

Distinct590
Distinct (%)7.9%
Missing0
Missing (%)0.0%
Memory size425.6 KiB
*
5250 
7
 
104
8
 
104
6
 
102
5
 
78
Other values (585)
1829 

Length

Max length7
Median length1
Mean length1.350341503
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique365 ?
Unique (%)4.9%

Sample

1st row1722595
2nd row9256
3rd row7162
4th row1755
5th row1165

Common Values

ValueCountFrequency (%)
*5250
70.3%
7104
 
1.4%
8104
 
1.4%
6102
 
1.4%
578
 
1.0%
1067
 
0.9%
1164
 
0.9%
964
 
0.9%
1247
 
0.6%
447
 
0.6%
Other values (580)1540
 
20.6%

Length

2022-11-06T21:07:42.274879image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
7104
 
1.4%
8104
 
1.4%
6102
 
1.4%
578
 
1.0%
1067
 
0.9%
1164
 
0.9%
964
 
0.9%
1247
 
0.6%
447
 
0.6%
Other values (580)1540
 
20.6%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p_18ymas_m
Categorical

HIGH CARDINALITY

Distinct451
Distinct (%)6.0%
Missing0
Missing (%)0.0%
Memory size425.0 KiB
*
5250 
3
 
178
4
 
164
5
 
138
6
 
121
Other values (446)
1616 

Length

Max length6
Median length1
Mean length1.266907727
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique267 ?
Unique (%)3.6%

Sample

1st row860242
2nd row5768
3rd row5488
4th row913
5th row620

Common Values

ValueCountFrequency (%)
*5250
70.3%
3178
 
2.4%
4164
 
2.2%
5138
 
1.8%
6121
 
1.6%
773
 
1.0%
873
 
1.0%
957
 
0.8%
1052
 
0.7%
252
 
0.7%
Other values (441)1309
 
17.5%

Length

2022-11-06T21:07:42.489874image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
3178
 
2.4%
4164
 
2.2%
5138
 
1.8%
6121
 
1.6%
773
 
1.0%
873
 
1.0%
957
 
0.8%
1052
 
0.7%
252
 
0.7%
Other values (441)1309
 
17.5%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p_18ymas_f
Categorical

HIGH CARDINALITY

Distinct437
Distinct (%)5.9%
Missing0
Missing (%)0.0%
Memory size424.9 KiB
*
5250 
3
 
193
4
 
179
2
 
126
5
 
111
Other values (432)
1608 

Length

Max length6
Median length1
Mean length1.247355029
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique256 ?
Unique (%)3.4%

Sample

1st row862353
2nd row3488
3rd row1674
4th row842
5th row545

Common Values

ValueCountFrequency (%)
*5250
70.3%
3193
 
2.6%
4179
 
2.4%
2126
 
1.7%
5111
 
1.5%
690
 
1.2%
784
 
1.1%
172
 
1.0%
850
 
0.7%
942
 
0.6%
Other values (427)1270
 
17.0%

Length

2022-11-06T21:07:42.682874image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
3193
 
2.6%
4179
 
2.4%
2126
 
1.7%
5111
 
1.5%
690
 
1.2%
784
 
1.1%
172
 
1.0%
850
 
0.7%
942
 
0.6%
Other values (427)1270
 
17.0%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p_3a5
Categorical

HIGH CARDINALITY

Distinct211
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size423.9 KiB
*
5250 
0
 
510
1
 
327
2
 
198
3
 
133
Other values (206)
1049 

Length

Max length6
Median length1
Mean length1.115441275
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique127 ?
Unique (%)1.7%

Sample

1st row155088
2nd row575
3rd row301
4th row139
5th row89

Common Values

ValueCountFrequency (%)
*5250
70.3%
0510
 
6.8%
1327
 
4.4%
2198
 
2.7%
3133
 
1.8%
479
 
1.1%
670
 
0.9%
565
 
0.9%
759
 
0.8%
846
 
0.6%
Other values (201)730
 
9.8%

Length

2022-11-06T21:07:42.892876image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
0510
 
6.8%
1327
 
4.4%
2198
 
2.7%
3133
 
1.8%
479
 
1.1%
670
 
0.9%
565
 
0.9%
759
 
0.8%
846
 
0.6%
Other values (201)730
 
9.8%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p_3a5_m
Categorical

HIGH CARDINALITY

Distinct166
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size423.6 KiB
*
5250 
0
734 
1
 
356
2
 
186
3
 
121
Other values (161)
820 

Length

Max length5
Median length1
Mean length1.08008571
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique102 ?
Unique (%)1.4%

Sample

1st row79197
2nd row273
3rd row155
4th row80
5th row48

Common Values

ValueCountFrequency (%)
*5250
70.3%
0734
 
9.8%
1356
 
4.8%
2186
 
2.5%
3121
 
1.6%
494
 
1.3%
588
 
1.2%
654
 
0.7%
738
 
0.5%
836
 
0.5%
Other values (156)510
 
6.8%

Length

2022-11-06T21:07:43.097883image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
0734
 
9.8%
1356
 
4.8%
2186
 
2.5%
3121
 
1.6%
494
 
1.3%
588
 
1.2%
654
 
0.7%
738
 
0.5%
836
 
0.5%
Other values (156)510
 
6.8%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p_3a5_f
Categorical

HIGH CARDINALITY

Distinct162
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size423.6 KiB
*
5250 
0
770 
1
 
355
2
 
194
3
 
106
Other values (157)
792 

Length

Max length5
Median length1
Mean length1.077809026
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique101 ?
Unique (%)1.4%

Sample

1st row75891
2nd row302
3rd row146
4th row59
5th row41

Common Values

ValueCountFrequency (%)
*5250
70.3%
0770
 
10.3%
1355
 
4.8%
2194
 
2.6%
3106
 
1.4%
479
 
1.1%
571
 
1.0%
665
 
0.9%
744
 
0.6%
840
 
0.5%
Other values (152)493
 
6.6%

Length

2022-11-06T21:07:43.289875image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
0770
 
10.3%
1355
 
4.8%
2194
 
2.6%
3106
 
1.4%
479
 
1.1%
571
 
1.0%
665
 
0.9%
744
 
0.6%
840
 
0.5%
Other values (152)493
 
6.6%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p_6a11
Categorical

HIGH CARDINALITY

Distinct291
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Memory size424.3 KiB
*
5250 
0
 
351
1
 
225
2
 
182
3
 
151
Other values (286)
1308 

Length

Max length6
Median length1
Mean length1.165260479
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique163 ?
Unique (%)2.2%

Sample

1st row314748
2nd row1062
3rd row528
4th row311
5th row210

Common Values

ValueCountFrequency (%)
*5250
70.3%
0351
 
4.7%
1225
 
3.0%
2182
 
2.4%
3151
 
2.0%
4121
 
1.6%
581
 
1.1%
668
 
0.9%
747
 
0.6%
937
 
0.5%
Other values (281)954
 
12.8%

Length

2022-11-06T21:07:43.459873image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
0351
 
4.7%
1225
 
3.0%
2182
 
2.4%
3151
 
2.0%
4121
 
1.6%
581
 
1.1%
668
 
0.9%
747
 
0.6%
937
 
0.5%
Other values (281)954
 
12.8%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p_6a11_m
Categorical

HIGH CARDINALITY

Distinct223
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size423.9 KiB
*
5250 
0
549 
1
 
279
2
 
218
3
 
119
Other values (218)
1052 

Length

Max length6
Median length1
Mean length1.120128566
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique131 ?
Unique (%)1.8%

Sample

1st row160718
2nd row567
3rd row295
4th row168
5th row106

Common Values

ValueCountFrequency (%)
*5250
70.3%
0549
 
7.4%
1279
 
3.7%
2218
 
2.9%
3119
 
1.6%
491
 
1.2%
563
 
0.8%
654
 
0.7%
747
 
0.6%
844
 
0.6%
Other values (213)753
 
10.1%

Length

2022-11-06T21:07:43.614879image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
0549
 
7.4%
1279
 
3.7%
2218
 
2.9%
3119
 
1.6%
491
 
1.2%
563
 
0.8%
654
 
0.7%
747
 
0.6%
844
 
0.6%
Other values (213)753
 
10.1%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p_6a11_f
Categorical

HIGH CARDINALITY

Distinct215
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size423.9 KiB
*
5250 
0
552 
1
 
333
2
 
202
3
 
115
Other values (210)
1015 

Length

Max length6
Median length1
Mean length1.116780501
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique123 ?
Unique (%)1.6%

Sample

1st row154030
2nd row495
3rd row233
4th row143
5th row104

Common Values

ValueCountFrequency (%)
*5250
70.3%
0552
 
7.4%
1333
 
4.5%
2202
 
2.7%
3115
 
1.5%
486
 
1.2%
566
 
0.9%
660
 
0.8%
840
 
0.5%
1135
 
0.5%
Other values (205)728
 
9.7%

Length

2022-11-06T21:07:43.780394image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
0552
 
7.4%
1333
 
4.5%
2202
 
2.7%
3115
 
1.5%
486
 
1.2%
566
 
0.9%
660
 
0.8%
840
 
0.5%
1135
 
0.5%
Other values (205)728
 
9.7%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p_8a14
Categorical

HIGH CARDINALITY

Distinct304
Distinct (%)4.1%
Missing0
Missing (%)0.0%
Memory size424.3 KiB
*
5250 
0
 
330
1
 
208
2
 
181
3
 
151
Other values (299)
1347 

Length

Max length6
Median length1
Mean length1.175706442
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique171 ?
Unique (%)2.3%

Sample

1st row363332
2nd row1262
3rd row629
4th row370
5th row251

Common Values

ValueCountFrequency (%)
*5250
70.3%
0330
 
4.4%
1208
 
2.8%
2181
 
2.4%
3151
 
2.0%
4113
 
1.5%
599
 
1.3%
654
 
0.7%
945
 
0.6%
742
 
0.6%
Other values (294)994
 
13.3%

Length

2022-11-06T21:07:43.959385image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
0330
 
4.4%
1208
 
2.8%
2181
 
2.4%
3151
 
2.0%
4113
 
1.5%
599
 
1.3%
654
 
0.7%
945
 
0.6%
742
 
0.6%
Other values (294)994
 
13.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p_8a14_m
Categorical

HIGH CARDINALITY

Distinct231
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size424.0 KiB
*
5250 
0
 
504
1
 
291
2
 
192
3
 
140
Other values (226)
1090 

Length

Max length6
Median length1
Mean length1.129770992
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique129 ?
Unique (%)1.7%

Sample

1st row185761
2nd row692
3rd row370
4th row214
5th row144

Common Values

ValueCountFrequency (%)
*5250
70.3%
0504
 
6.7%
1291
 
3.9%
2192
 
2.6%
3140
 
1.9%
490
 
1.2%
572
 
1.0%
651
 
0.7%
842
 
0.6%
740
 
0.5%
Other values (221)795
 
10.6%

Length

2022-11-06T21:07:44.252359image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
0504
 
6.7%
1291
 
3.9%
2192
 
2.6%
3140
 
1.9%
490
 
1.2%
572
 
1.0%
651
 
0.7%
842
 
0.6%
740
 
0.5%
Other values (221)795
 
10.6%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p_8a14_f
Categorical

HIGH CARDINALITY

Distinct226
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size424.0 KiB
*
5250 
0
530 
1
 
306
2
 
206
3
 
125
Other values (221)
1050 

Length

Max length6
Median length1
Mean length1.124414089
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique131 ?
Unique (%)1.8%

Sample

1st row177571
2nd row570
3rd row259
4th row156
5th row107

Common Values

ValueCountFrequency (%)
*5250
70.3%
0530
 
7.1%
1306
 
4.1%
2206
 
2.8%
3125
 
1.7%
490
 
1.2%
658
 
0.8%
746
 
0.6%
546
 
0.6%
940
 
0.5%
Other values (216)770
 
10.3%

Length

2022-11-06T21:07:44.421359image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
0530
 
7.1%
1306
 
4.1%
2206
 
2.8%
3125
 
1.7%
490
 
1.2%
658
 
0.8%
746
 
0.6%
546
 
0.6%
940
 
0.5%
Other values (216)770
 
10.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p_12a14
Categorical

HIGH CARDINALITY

Distinct211
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size423.9 KiB
*
5250 
0
573 
1
 
322
2
 
210
3
 
120
Other values (206)
992 

Length

Max length6
Median length1
Mean length1.115441275
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique120 ?
Unique (%)1.6%

Sample

1st row151436
2nd row549
3rd row289
4th row162
5th row111

Common Values

ValueCountFrequency (%)
*5250
70.3%
0573
 
7.7%
1322
 
4.3%
2210
 
2.8%
3120
 
1.6%
476
 
1.0%
562
 
0.8%
751
 
0.7%
643
 
0.6%
838
 
0.5%
Other values (201)722
 
9.7%

Length

2022-11-06T21:07:44.579360image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
0573
 
7.7%
1322
 
4.3%
2210
 
2.8%
3120
 
1.6%
476
 
1.0%
562
 
0.8%
751
 
0.7%
643
 
0.6%
838
 
0.5%
Other values (201)722
 
9.7%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p_12a14_m
Categorical

HIGH CARDINALITY

Distinct160
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size423.6 KiB
*
5250 
0
796 
1
 
356
2
 
171
3
 
95
Other values (155)
799 

Length

Max length5
Median length1
Mean length1.079416097
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique93 ?
Unique (%)1.2%

Sample

1st row77362
2nd row292
3rd row177
4th row92
5th row68

Common Values

ValueCountFrequency (%)
*5250
70.3%
0796
 
10.7%
1356
 
4.8%
2171
 
2.3%
395
 
1.3%
485
 
1.1%
562
 
0.8%
761
 
0.8%
655
 
0.7%
1039
 
0.5%
Other values (150)497
 
6.7%

Length

2022-11-06T21:07:44.743384image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
0796
 
10.7%
1356
 
4.8%
2171
 
2.3%
395
 
1.3%
485
 
1.1%
562
 
0.8%
761
 
0.8%
655
 
0.7%
1039
 
0.5%
Other values (150)497
 
6.7%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p_12a14_f
Categorical

HIGH CARDINALITY

Distinct167
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size423.6 KiB
*
5250 
0
835 
1
 
343
2
 
165
3
 
103
Other values (162)
771 

Length

Max length5
Median length1
Mean length1.078612562
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique109 ?
Unique (%)1.5%

Sample

1st row74074
2nd row257
3rd row112
4th row70
5th row43

Common Values

ValueCountFrequency (%)
*5250
70.3%
0835
 
11.2%
1343
 
4.6%
2165
 
2.2%
3103
 
1.4%
478
 
1.0%
558
 
0.8%
847
 
0.6%
744
 
0.6%
643
 
0.6%
Other values (157)501
 
6.7%

Length

2022-11-06T21:07:44.929390image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
0835
 
11.2%
1343
 
4.6%
2165
 
2.2%
3103
 
1.4%
478
 
1.0%
558
 
0.8%
847
 
0.6%
744
 
0.6%
643
 
0.6%
Other values (157)501
 
6.7%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p_15a17
Categorical

HIGH CARDINALITY

Distinct217
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size423.9 KiB
*
5250 
0
531 
1
 
352
2
 
180
3
 
144
Other values (212)
1010 

Length

Max length6
Median length1
Mean length1.11878934
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique126 ?
Unique (%)1.7%

Sample

1st row151792
2nd row536
3rd row396
4th row141
5th row94

Common Values

ValueCountFrequency (%)
*5250
70.3%
0531
 
7.1%
1352
 
4.7%
2180
 
2.4%
3144
 
1.9%
476
 
1.0%
557
 
0.8%
749
 
0.7%
645
 
0.6%
1236
 
0.5%
Other values (207)747
 
10.0%

Length

2022-11-06T21:07:45.120357image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
0531
 
7.1%
1352
 
4.7%
2180
 
2.4%
3144
 
1.9%
476
 
1.0%
557
 
0.8%
749
 
0.7%
645
 
0.6%
1236
 
0.5%
Other values (207)747
 
10.0%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p_15a17_m
Categorical

HIGH CARDINALITY

Distinct166
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size423.7 KiB
*
5250 
0
764 
1
 
341
2
 
187
3
 
109
Other values (161)
816 

Length

Max length5
Median length1
Mean length1.081157091
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique102 ?
Unique (%)1.4%

Sample

1st row77357
2nd row306
3rd row261
4th row80
5th row50

Common Values

ValueCountFrequency (%)
*5250
70.3%
0764
 
10.2%
1341
 
4.6%
2187
 
2.5%
3109
 
1.5%
470
 
0.9%
569
 
0.9%
661
 
0.8%
761
 
0.8%
937
 
0.5%
Other values (156)518
 
6.9%

Length

2022-11-06T21:07:45.309386image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
0764
 
10.2%
1341
 
4.6%
2187
 
2.5%
3109
 
1.5%
470
 
0.9%
569
 
0.9%
661
 
0.8%
761
 
0.8%
937
 
0.5%
Other values (156)518
 
6.9%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p_15a17_f
Categorical

HIGH CARDINALITY

Distinct154
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size423.6 KiB
*
5250 
0
794 
1
 
367
2
 
184
3
 
89
Other values (149)
783 

Length

Max length5
Median length1
Mean length1.077005491
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique91 ?
Unique (%)1.2%

Sample

1st row74435
2nd row230
3rd row135
4th row61
5th row44

Common Values

ValueCountFrequency (%)
*5250
70.3%
0794
 
10.6%
1367
 
4.9%
2184
 
2.5%
389
 
1.2%
478
 
1.0%
565
 
0.9%
658
 
0.8%
746
 
0.6%
940
 
0.5%
Other values (144)496
 
6.6%

Length

2022-11-06T21:07:45.498405image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
0794
 
10.6%
1367
 
4.9%
2184
 
2.5%
389
 
1.2%
478
 
1.0%
565
 
0.9%
658
 
0.8%
746
 
0.6%
940
 
0.5%
Other values (144)496
 
6.6%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p_18a24
Categorical

HIGH CARDINALITY

Distinct283
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size424.3 KiB
*
5250 
0
 
312
1
 
238
2
 
218
3
 
147
Other values (278)
1302 

Length

Max length6
Median length1
Mean length1.167269318
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique159 ?
Unique (%)2.1%

Sample

1st row327865
2nd row1170
3rd row1353
4th row279
5th row172

Common Values

ValueCountFrequency (%)
*5250
70.3%
0312
 
4.2%
1238
 
3.2%
2218
 
2.9%
3147
 
2.0%
497
 
1.3%
571
 
1.0%
768
 
0.9%
654
 
0.7%
842
 
0.6%
Other values (273)970
 
13.0%

Length

2022-11-06T21:07:45.667734image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
0312
 
4.2%
1238
 
3.2%
2218
 
2.9%
3147
 
2.0%
497
 
1.3%
571
 
1.0%
768
 
0.9%
654
 
0.7%
842
 
0.6%
Other values (273)970
 
13.0%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p_18a24_m
Categorical

HIGH CARDINALITY

Distinct222
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size423.9 KiB
*
5250 
0
 
505
1
 
327
2
 
187
3
 
128
Other values (217)
1070 

Length

Max length6
Median length1
Mean length1.120128566
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique127 ?
Unique (%)1.7%

Sample

1st row167369
2nd row639
3rd row1041
4th row147
5th row93

Common Values

ValueCountFrequency (%)
*5250
70.3%
0505
 
6.8%
1327
 
4.4%
2187
 
2.5%
3128
 
1.7%
486
 
1.2%
579
 
1.1%
759
 
0.8%
650
 
0.7%
847
 
0.6%
Other values (212)749
 
10.0%

Length

2022-11-06T21:07:45.823735image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
0505
 
6.8%
1327
 
4.4%
2187
 
2.5%
3128
 
1.7%
486
 
1.2%
579
 
1.1%
759
 
0.8%
650
 
0.7%
847
 
0.6%
Other values (212)749
 
10.0%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p_18a24_f
Categorical

HIGH CARDINALITY

Distinct210
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size423.9 KiB
*
5250 
0
 
501
1
 
375
2
 
192
3
 
137
Other values (205)
1012 

Length

Max length6
Median length1
Mean length1.1126289
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique127 ?
Unique (%)1.7%

Sample

1st row160496
2nd row531
3rd row312
4th row132
5th row79

Common Values

ValueCountFrequency (%)
*5250
70.3%
0501
 
6.7%
1375
 
5.0%
2192
 
2.6%
3137
 
1.8%
497
 
1.3%
858
 
0.8%
556
 
0.7%
656
 
0.7%
940
 
0.5%
Other values (200)705
 
9.4%

Length

2022-11-06T21:07:45.983736image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
0501
 
6.7%
1375
 
5.0%
2192
 
2.6%
3137
 
1.8%
497
 
1.3%
858
 
0.8%
556
 
0.7%
656
 
0.7%
940
 
0.5%
Other values (200)705
 
9.4%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p_15a49_f
Categorical

HIGH CARDINALITY

Distinct398
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Memory size424.7 KiB
*
5250 
2
 
184
3
 
183
4
 
153
1
 
129
Other values (393)
1568 

Length

Max length6
Median length1
Mean length1.222579349
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique243 ?
Unique (%)3.3%

Sample

1st row702083
2nd row2316
3rd row1267
4th row614
5th row403

Common Values

ValueCountFrequency (%)
*5250
70.3%
2184
 
2.5%
3183
 
2.5%
4153
 
2.0%
1129
 
1.7%
5100
 
1.3%
090
 
1.2%
685
 
1.1%
756
 
0.7%
851
 
0.7%
Other values (388)1186
 
15.9%

Length

2022-11-06T21:07:46.149736image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
2184
 
2.5%
3183
 
2.5%
4153
 
2.0%
1129
 
1.7%
5100
 
1.3%
090
 
1.2%
685
 
1.1%
756
 
0.7%
851
 
0.7%
Other values (388)1186
 
15.9%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p_60ymas
Categorical

HIGH CARDINALITY

Distinct295
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size424.3 KiB
*
5250 
0
 
280
1
 
249
2
 
216
3
 
157
Other values (290)
1315 

Length

Max length6
Median length1
Mean length1.169546002
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique170 ?
Unique (%)2.3%

Sample

1st row232874
2nd row2518
3rd row816
4th row367
5th row244

Common Values

ValueCountFrequency (%)
*5250
70.3%
0280
 
3.7%
1249
 
3.3%
2216
 
2.9%
3157
 
2.1%
4113
 
1.5%
663
 
0.8%
557
 
0.8%
749
 
0.7%
938
 
0.5%
Other values (285)995
 
13.3%

Length

2022-11-06T21:07:46.349737image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
0280
 
3.7%
1249
 
3.3%
2216
 
2.9%
3157
 
2.1%
4113
 
1.5%
663
 
0.8%
557
 
0.8%
749
 
0.7%
938
 
0.5%
Other values (285)995
 
13.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p_60ymas_m
Categorical

HIGH CARDINALITY

Distinct228
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size424.0 KiB
*
5250 
0
 
379
1
 
349
2
 
231
3
 
147
Other values (223)
1111 

Length

Max length6
Median length1
Mean length1.129503147
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique127 ?
Unique (%)1.7%

Sample

1st row112175
2nd row1719
3rd row541
4th row204
5th row136

Common Values

ValueCountFrequency (%)
*5250
70.3%
0379
 
5.1%
1349
 
4.7%
2231
 
3.1%
3147
 
2.0%
495
 
1.3%
569
 
0.9%
652
 
0.7%
745
 
0.6%
842
 
0.6%
Other values (218)808
 
10.8%

Length

2022-11-06T21:07:46.547733image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
0379
 
5.1%
1349
 
4.7%
2231
 
3.1%
3147
 
2.0%
495
 
1.3%
569
 
0.9%
652
 
0.7%
745
 
0.6%
842
 
0.6%
Other values (218)808
 
10.8%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p_60ymas_f
Categorical

HIGH CARDINALITY

Distinct217
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size423.9 KiB
*
5250 
0
565 
1
 
358
2
 
185
3
 
100
Other values (212)
1009 

Length

Max length6
Median length1
Mean length1.117985804
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique124 ?
Unique (%)1.7%

Sample

1st row120699
2nd row799
3rd row275
4th row163
5th row108

Common Values

ValueCountFrequency (%)
*5250
70.3%
0565
 
7.6%
1358
 
4.8%
2185
 
2.5%
3100
 
1.3%
479
 
1.1%
577
 
1.0%
1047
 
0.6%
645
 
0.6%
937
 
0.5%
Other values (207)724
 
9.7%

Length

2022-11-06T21:07:46.733736image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
0565
 
7.6%
1358
 
4.8%
2185
 
2.5%
3100
 
1.3%
479
 
1.1%
577
 
1.0%
1047
 
0.6%
645
 
0.6%
937
 
0.5%
Other values (207)724
 
9.7%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

rel_h_m
Categorical

HIGH CARDINALITY

Distinct934
Distinct (%)12.5%
Missing0
Missing (%)0.0%
Memory size430.9 KiB
*
5376 
100
 
124
150
 
64
200
 
55
133.33
 
40
Other values (929)
1808 

Length

Max length6
Median length1
Mean length2.076737646
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique701 ?
Unique (%)9.4%

Sample

1st row101.27
2nd row*
3rd row*
4th row114.04
5th row115.47

Common Values

ValueCountFrequency (%)
*5376
72.0%
100124
 
1.7%
15064
 
0.9%
20055
 
0.7%
133.3340
 
0.5%
166.6738
 
0.5%
12535
 
0.5%
30030
 
0.4%
12024
 
0.3%
25023
 
0.3%
Other values (924)1658
 
22.2%

Length

2022-11-06T21:07:46.933736image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5376
72.0%
100124
 
1.7%
15064
 
0.9%
20055
 
0.7%
133.3340
 
0.5%
166.6738
 
0.5%
12535
 
0.5%
30030
 
0.4%
12024
 
0.3%
25023
 
0.3%
Other values (924)1658
 
22.2%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

pob0_14
Categorical

HIGH CARDINALITY

Distinct418
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Memory size424.8 KiB
*
5250 
0
 
162
3
 
130
2
 
116
4
 
107
Other values (413)
1702 

Length

Max length6
Median length1
Mean length1.243471274
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique240 ?
Unique (%)3.2%

Sample

1st row767802
2nd row2715
3rd row1422
4th row737
5th row478

Common Values

ValueCountFrequency (%)
*5250
70.3%
0162
 
2.2%
3130
 
1.7%
2116
 
1.6%
4107
 
1.4%
1104
 
1.4%
597
 
1.3%
686
 
1.2%
775
 
1.0%
858
 
0.8%
Other values (408)1282
 
17.2%

Length

2022-11-06T21:07:47.118732image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
0162
 
2.2%
3130
 
1.7%
2116
 
1.6%
4107
 
1.4%
1104
 
1.4%
597
 
1.3%
686
 
1.2%
775
 
1.0%
858
 
0.8%
Other values (408)1282
 
17.2%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

pob15_64
Categorical

HIGH CARDINALITY

Distinct564
Distinct (%)7.6%
Missing0
Missing (%)0.0%
Memory size425.5 KiB
*
5250 
6
 
100
7
 
96
8
 
93
5
 
77
Other values (559)
1851 

Length

Max length7
Median length1
Mean length1.340029463
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique324 ?
Unique (%)4.3%

Sample

1st row1715956
2nd row8040
3rd row6990
4th row1625
5th row1080

Common Values

ValueCountFrequency (%)
*5250
70.3%
6100
 
1.3%
796
 
1.3%
893
 
1.2%
577
 
1.0%
968
 
0.9%
1065
 
0.9%
461
 
0.8%
1152
 
0.7%
1345
 
0.6%
Other values (554)1560
 
20.9%

Length

2022-11-06T21:07:47.328732image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
6100
 
1.3%
796
 
1.3%
893
 
1.2%
577
 
1.0%
968
 
0.9%
1065
 
0.9%
461
 
0.8%
1152
 
0.7%
1345
 
0.6%
Other values (554)1560
 
20.9%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

pob65_mas
Categorical

HIGH CARDINALITY

Distinct260
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Memory size424.1 KiB
*
5250 
0
 
404
1
 
293
2
 
215
3
 
124
Other values (255)
1181 

Length

Max length6
Median length1
Mean length1.146779162
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique149 ?
Unique (%)2.0%

Sample

1st row158431
2nd row1752
3rd row568
4th row271
5th row179

Common Values

ValueCountFrequency (%)
*5250
70.3%
0404
 
5.4%
1293
 
3.9%
2215
 
2.9%
3124
 
1.7%
493
 
1.2%
563
 
0.8%
655
 
0.7%
750
 
0.7%
1038
 
0.5%
Other values (250)882
 
11.8%

Length

2022-11-06T21:07:47.517732image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
0404
 
5.4%
1293
 
3.9%
2215
 
2.9%
3124
 
1.7%
493
 
1.2%
563
 
0.8%
655
 
0.7%
750
 
0.7%
1038
 
0.5%
Other values (250)882
 
11.8%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

prom_hnv
Categorical

HIGH CARDINALITY

Distinct320
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size428.0 KiB
*
5376 
3
 
91
2
 
81
2.5
 
49
4
 
39
Other values (315)
1831 

Length

Max length4
Median length1
Mean length1.673094951
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique76 ?
Unique (%)1.0%

Sample

1st row2.3
2nd row*
3rd row*
4th row2.68
5th row2.66

Common Values

ValueCountFrequency (%)
*5376
72.0%
391
 
1.2%
281
 
1.1%
2.549
 
0.7%
439
 
0.5%
2.3334
 
0.5%
2.7533
 
0.4%
1.529
 
0.4%
2.6729
 
0.4%
127
 
0.4%
Other values (310)1679
 
22.5%

Length

2022-11-06T21:07:47.709731image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5376
72.0%
391
 
1.2%
281
 
1.1%
2.549
 
0.7%
439
 
0.5%
2.3334
 
0.5%
2.7533
 
0.4%
2.6729
 
0.4%
1.529
 
0.4%
127
 
0.4%
Other values (310)1679
 
22.5%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

pnacent
Categorical

HIGH CARDINALITY

Distinct661
Distinct (%)8.9%
Missing0
Missing (%)0.0%
Memory size425.8 KiB
*
5250 
9
 
74
7
 
68
8
 
68
6
 
60
Other values (656)
1947 

Length

Max length7
Median length1
Mean length1.381679389
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique426 ?
Unique (%)5.7%

Sample

1st row2175694
2nd row10399
3rd row6598
4th row2591
5th row1715

Common Values

ValueCountFrequency (%)
*5250
70.3%
974
 
1.0%
768
 
0.9%
868
 
0.9%
660
 
0.8%
1158
 
0.8%
1357
 
0.8%
1654
 
0.7%
1050
 
0.7%
448
 
0.6%
Other values (651)1680
 
22.5%

Length

2022-11-06T21:07:47.895737image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
974
 
1.0%
768
 
0.9%
868
 
0.9%
660
 
0.8%
1158
 
0.8%
1357
 
0.8%
1654
 
0.7%
1050
 
0.7%
448
 
0.6%
Other values (651)1680
 
22.5%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

pnacent_m
Categorical

HIGH CARDINALITY

Distinct502
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size425.2 KiB
*
5250 
5
 
136
6
 
119
3
 
115
4
 
93
Other values (497)
1754 

Length

Max length7
Median length1
Mean length1.291147717
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique292 ?
Unique (%)3.9%

Sample

1st row1089086
2nd row6182
3rd row4599
4th row1385
5th row920

Common Values

ValueCountFrequency (%)
*5250
70.3%
5136
 
1.8%
6119
 
1.6%
3115
 
1.5%
493
 
1.2%
774
 
1.0%
971
 
1.0%
271
 
1.0%
861
 
0.8%
1055
 
0.7%
Other values (492)1422
 
19.0%

Length

2022-11-06T21:07:48.077734image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
5136
 
1.8%
6119
 
1.6%
3115
 
1.5%
493
 
1.2%
774
 
1.0%
971
 
1.0%
271
 
1.0%
861
 
0.8%
1055
 
0.7%
Other values (492)1422
 
19.0%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

pnacent_f
Categorical

HIGH CARDINALITY

Distinct486
Distinct (%)6.5%
Missing0
Missing (%)0.0%
Memory size425.1 KiB
*
5250 
4
 
122
3
 
121
5
 
97
2
 
96
Other values (481)
1781 

Length

Max length7
Median length1
Mean length1.273603857
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique289 ?
Unique (%)3.9%

Sample

1st row1086608
2nd row4217
3rd row1999
4th row1206
5th row795

Common Values

ValueCountFrequency (%)
*5250
70.3%
4122
 
1.6%
3121
 
1.6%
597
 
1.3%
296
 
1.3%
691
 
1.2%
180
 
1.1%
778
 
1.0%
872
 
1.0%
969
 
0.9%
Other values (476)1391
 
18.6%

Length

2022-11-06T21:07:48.294732image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
4122
 
1.6%
3121
 
1.6%
597
 
1.3%
296
 
1.3%
691
 
1.2%
180
 
1.1%
778
 
1.0%
872
 
1.0%
969
 
0.9%
Other values (476)1391
 
18.6%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

pnacoe
Categorical

HIGH CARDINALITY

Distinct268
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size424.1 KiB
*
5250 
0
 
512
1
 
242
2
 
153
3
 
128
Other values (263)
1182 

Length

Max length6
Median length1
Mean length1.136065354
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique167 ?
Unique (%)2.2%

Sample

1st row417237
2nd row1951
3rd row2251
4th row18
5th row13

Common Values

ValueCountFrequency (%)
*5250
70.3%
0512
 
6.9%
1242
 
3.2%
2153
 
2.0%
3128
 
1.7%
4102
 
1.4%
591
 
1.2%
682
 
1.1%
767
 
0.9%
852
 
0.7%
Other values (258)788
 
10.6%

Length

2022-11-06T21:07:48.509739image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
0512
 
6.9%
1242
 
3.2%
2153
 
2.0%
3128
 
1.7%
4102
 
1.4%
591
 
1.2%
682
 
1.1%
767
 
0.9%
852
 
0.7%
Other values (258)788
 
10.6%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

pnacoe_m
Categorical

HIGH CARDINALITY

Distinct219
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size423.8 KiB
*
5250 
0
638 
1
 
325
2
 
179
3
 
155
Other values (214)
920 

Length

Max length6
Median length1
Mean length1.096424267
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique142 ?
Unique (%)1.9%

Sample

1st row214923
2nd row1212
3rd row1843
4th row9
5th row7

Common Values

ValueCountFrequency (%)
*5250
70.3%
0638
 
8.5%
1325
 
4.4%
2179
 
2.4%
3155
 
2.1%
4109
 
1.5%
582
 
1.1%
662
 
0.8%
752
 
0.7%
848
 
0.6%
Other values (209)567
 
7.6%

Length

2022-11-06T21:07:48.691736image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
0638
 
8.5%
1325
 
4.4%
2179
 
2.4%
3155
 
2.1%
4109
 
1.5%
582
 
1.1%
662
 
0.8%
752
 
0.7%
848
 
0.6%
Other values (209)567
 
7.6%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

pnacoe_f
Categorical

HIGH CARDINALITY

Distinct195
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size423.7 KiB
*
5250 
0
755 
1
 
278
2
 
206
3
 
147
Other values (190)
831 

Length

Max length6
Median length1
Mean length1.088924602
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique112 ?
Unique (%)1.5%

Sample

1st row202314
2nd row739
3rd row408
4th row9
5th row6

Common Values

ValueCountFrequency (%)
*5250
70.3%
0755
 
10.1%
1278
 
3.7%
2206
 
2.8%
3147
 
2.0%
499
 
1.3%
578
 
1.0%
658
 
0.8%
838
 
0.5%
933
 
0.4%
Other values (185)525
 
7.0%

Length

2022-11-06T21:07:48.875736image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
0755
 
10.1%
1278
 
3.7%
2206
 
2.8%
3147
 
2.0%
499
 
1.3%
578
 
1.0%
658
 
0.8%
838
 
0.5%
733
 
0.4%
Other values (185)525
 
7.0%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

pres2005
Categorical

HIGH CARDINALITY

Distinct638
Distinct (%)8.5%
Missing0
Missing (%)0.0%
Memory size425.9 KiB
*
5250 
8
 
76
10
 
72
7
 
67
11
 
59
Other values (633)
1943 

Length

Max length7
Median length1
Mean length1.389714745
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique380 ?
Unique (%)5.1%

Sample

1st row2260965
2nd row10950
3rd row7390
4th row2392
5th row1605

Common Values

ValueCountFrequency (%)
*5250
70.3%
876
 
1.0%
1072
 
1.0%
767
 
0.9%
1159
 
0.8%
954
 
0.7%
1254
 
0.7%
652
 
0.7%
1445
 
0.6%
1542
 
0.6%
Other values (628)1696
 
22.7%

Length

2022-11-06T21:07:49.278748image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
876
 
1.0%
1072
 
1.0%
767
 
0.9%
1159
 
0.8%
1254
 
0.7%
954
 
0.7%
652
 
0.7%
1445
 
0.6%
1542
 
0.6%
Other values (628)1696
 
22.7%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

pres2005_m
Categorical

HIGH CARDINALITY

Distinct503
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size425.2 KiB
*
5250 
4
 
126
6
 
126
5
 
110
3
 
99
Other values (498)
1756 

Length

Max length7
Median length1
Mean length1.298111691
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique298 ?
Unique (%)4.0%

Sample

1st row1128878
2nd row6622
3rd row5348
4th row1263
5th row855

Common Values

ValueCountFrequency (%)
*5250
70.3%
4126
 
1.7%
6126
 
1.7%
5110
 
1.5%
399
 
1.3%
775
 
1.0%
872
 
1.0%
971
 
1.0%
1158
 
0.8%
1052
 
0.7%
Other values (493)1428
 
19.1%

Length

2022-11-06T21:07:49.515733image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
4126
 
1.7%
6126
 
1.7%
5110
 
1.5%
399
 
1.3%
775
 
1.0%
872
 
1.0%
971
 
1.0%
1158
 
0.8%
1052
 
0.7%
Other values (493)1428
 
19.1%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

pres2005_f
Categorical

HIGH CARDINALITY

Distinct487
Distinct (%)6.5%
Missing0
Missing (%)0.0%
Memory size425.1 KiB
*
5250 
4
 
123
5
 
117
3
 
112
2
 
97
Other values (482)
1768 

Length

Max length7
Median length1
Mean length1.275880541
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique286 ?
Unique (%)3.8%

Sample

1st row1132087
2nd row4328
3rd row2042
4th row1129
5th row750

Common Values

ValueCountFrequency (%)
*5250
70.3%
4123
 
1.6%
5117
 
1.6%
3112
 
1.5%
297
 
1.3%
791
 
1.2%
685
 
1.1%
882
 
1.1%
162
 
0.8%
961
 
0.8%
Other values (477)1387
 
18.6%

Length

2022-11-06T21:07:49.709733image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
4123
 
1.6%
5117
 
1.6%
3112
 
1.5%
297
 
1.3%
791
 
1.2%
685
 
1.1%
882
 
1.1%
162
 
0.8%
961
 
0.8%
Other values (477)1387
 
18.6%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

presoe05
Categorical

HIGH CARDINALITY

Distinct147
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size423.5 KiB
*
5250 
0
1255 
1
 
210
2
 
134
3
 
76
Other values (142)
542 

Length

Max length5
Median length1
Mean length1.058925941
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique89 ?
Unique (%)1.2%

Sample

1st row78545
2nd row411
3rd row788
4th row1
5th row0

Common Values

ValueCountFrequency (%)
*5250
70.3%
01255
 
16.8%
1210
 
2.8%
2134
 
1.8%
376
 
1.0%
466
 
0.9%
548
 
0.6%
640
 
0.5%
1027
 
0.4%
725
 
0.3%
Other values (137)336
 
4.5%

Length

2022-11-06T21:07:49.894734image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
01255
 
16.8%
1210
 
2.8%
2134
 
1.8%
376
 
1.0%
466
 
0.9%
548
 
0.6%
640
 
0.5%
1027
 
0.4%
725
 
0.3%
Other values (137)336
 
4.5%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

presoe05_m
Categorical

HIGH CARDINALITY

Distinct128
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size423.3 KiB
*
5250 
0
1369 
1
 
259
2
 
131
3
 
71
Other values (123)
 
387

Length

Max length5
Median length1
Mean length1.03923932
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique85 ?
Unique (%)1.1%

Sample

1st row42601
2nd row260
3rd row663
4th row1
5th row0

Common Values

ValueCountFrequency (%)
*5250
70.3%
01369
 
18.3%
1259
 
3.5%
2131
 
1.8%
371
 
1.0%
446
 
0.6%
536
 
0.5%
633
 
0.4%
731
 
0.4%
816
 
0.2%
Other values (118)225
 
3.0%

Length

2022-11-06T21:07:50.098715image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
01369
 
18.3%
1259
 
3.5%
2131
 
1.8%
371
 
1.0%
446
 
0.6%
536
 
0.5%
633
 
0.4%
731
 
0.4%
816
 
0.2%
Other values (118)225
 
3.0%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

presoe05_f
Categorical

HIGH CARDINALITY

Distinct108
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size423.3 KiB
*
5250 
0
1427 
1
 
225
2
 
127
3
 
81
Other values (103)
 
357

Length

Max length5
Median length1
Mean length1.036962636
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique63 ?
Unique (%)0.8%

Sample

1st row35944
2nd row151
3rd row125
4th row0
5th row0

Common Values

ValueCountFrequency (%)
*5250
70.3%
01427
 
19.1%
1225
 
3.0%
2127
 
1.7%
381
 
1.1%
446
 
0.6%
530
 
0.4%
629
 
0.4%
720
 
0.3%
917
 
0.2%
Other values (98)215
 
2.9%

Length

2022-11-06T21:07:50.310714image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
01427
 
19.1%
1225
 
3.0%
2127
 
1.7%
381
 
1.1%
446
 
0.6%
530
 
0.4%
629
 
0.4%
720
 
0.3%
917
 
0.2%
Other values (98)215
 
2.9%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p3ym_hli
Categorical

HIGH CARDINALITY

Distinct217
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size423.7 KiB
*
5250 
0
1131 
1
 
244
2
 
125
3
 
75
Other values (212)
642 

Length

Max length5
Median length1
Mean length1.087987143
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique125 ?
Unique (%)1.7%

Sample

1st row61270
2nd row550
3rd row352
4th row1
5th row1

Common Values

ValueCountFrequency (%)
*5250
70.3%
01131
 
15.1%
1244
 
3.3%
2125
 
1.7%
375
 
1.0%
442
 
0.6%
536
 
0.5%
628
 
0.4%
725
 
0.3%
819
 
0.3%
Other values (207)492
 
6.6%

Length

2022-11-06T21:07:50.540717image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
01131
 
15.1%
1244
 
3.3%
2125
 
1.7%
375
 
1.0%
442
 
0.6%
536
 
0.5%
628
 
0.4%
725
 
0.3%
819
 
0.3%
Other values (207)492
 
6.6%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p3ym_hli_m
Categorical

HIGH CARDINALITY

Distinct175
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size423.6 KiB
*
5250 
0
1230 
1
 
273
2
 
106
3
 
56
Other values (170)
552 

Length

Max length5
Median length1
Mean length1.068032677
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique101 ?
Unique (%)1.4%

Sample

1st row33738
2nd row334
3rd row247
4th row1
5th row1

Common Values

ValueCountFrequency (%)
*5250
70.3%
01230
 
16.5%
1273
 
3.7%
2106
 
1.4%
356
 
0.7%
444
 
0.6%
534
 
0.5%
627
 
0.4%
821
 
0.3%
719
 
0.3%
Other values (165)407
 
5.5%

Length

2022-11-06T21:07:50.719712image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
01230
 
16.5%
1273
 
3.7%
2106
 
1.4%
356
 
0.7%
444
 
0.6%
534
 
0.5%
627
 
0.4%
821
 
0.3%
719
 
0.3%
Other values (165)407
 
5.5%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p3ym_hli_f
Categorical

HIGH CARDINALITY

Distinct152
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size423.5 KiB
*
5250 
0
1352 
1
 
231
2
 
80
3
 
60
Other values (147)
 
494

Length

Max length5
Median length1
Mean length1.060131244
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique80 ?
Unique (%)1.1%

Sample

1st row27532
2nd row216
3rd row105
4th row0
5th row0

Common Values

ValueCountFrequency (%)
*5250
70.3%
01352
 
18.1%
1231
 
3.1%
280
 
1.1%
360
 
0.8%
438
 
0.5%
827
 
0.4%
526
 
0.3%
721
 
0.3%
1416
 
0.2%
Other values (142)366
 
4.9%

Length

2022-11-06T21:07:50.902714image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
01352
 
18.1%
1231
 
3.1%
280
 
1.1%
360
 
0.8%
438
 
0.5%
827
 
0.4%
526
 
0.3%
721
 
0.3%
1416
 
0.2%
Other values (142)366
 
4.9%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p3hlinhe
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct40
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size423.1 KiB
*
5250 
0
2053 
1
 
64
2
 
22
3
 
15
Other values (35)
 
63

Length

Max length4
Median length1
Mean length1.005490826
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique27 ?
Unique (%)0.4%

Sample

1st row1419
2nd row10
3rd row10
4th row0
5th row0

Common Values

ValueCountFrequency (%)
*5250
70.3%
02053
 
27.5%
164
 
0.9%
222
 
0.3%
315
 
0.2%
67
 
0.1%
47
 
0.1%
56
 
0.1%
96
 
0.1%
84
 
0.1%
Other values (30)33
 
0.4%

Length

2022-11-06T21:07:51.073717image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
02053
 
27.5%
164
 
0.9%
222
 
0.3%
315
 
0.2%
67
 
0.1%
47
 
0.1%
96
 
0.1%
56
 
0.1%
84
 
0.1%
Other values (30)33
 
0.4%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p3hlinhe_m
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct26
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size423.1 KiB
*
5250 
0
2113 
1
 
37
2
 
14
3
 
13
Other values (21)
 
40

Length

Max length3
Median length1
Mean length1.003883755
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique14 ?
Unique (%)0.2%

Sample

1st row585
2nd row3
3rd row4
4th row0
5th row0

Common Values

ValueCountFrequency (%)
*5250
70.3%
02113
28.3%
137
 
0.5%
214
 
0.2%
313
 
0.2%
49
 
0.1%
115
 
0.1%
123
 
< 0.1%
203
 
< 0.1%
82
 
< 0.1%
Other values (16)18
 
0.2%

Length

2022-11-06T21:07:51.266717image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
02113
28.3%
137
 
0.5%
214
 
0.2%
313
 
0.2%
49
 
0.1%
115
 
0.1%
123
 
< 0.1%
203
 
< 0.1%
82
 
< 0.1%
Other values (16)18
 
0.2%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p3hlinhe_f
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct30
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size423.1 KiB
*
5250 
0
2077 
1
 
60
2
 
25
3
 
10
Other values (25)
 
45

Length

Max length3
Median length1
Mean length1.004419446
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique16 ?
Unique (%)0.2%

Sample

1st row834
2nd row7
3rd row6
4th row0
5th row0

Common Values

ValueCountFrequency (%)
*5250
70.3%
02077
 
27.8%
160
 
0.8%
225
 
0.3%
310
 
0.1%
68
 
0.1%
54
 
0.1%
44
 
0.1%
273
 
< 0.1%
162
 
< 0.1%
Other values (20)24
 
0.3%

Length

2022-11-06T21:07:51.451727image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
02077
 
27.8%
160
 
0.8%
225
 
0.3%
310
 
0.1%
68
 
0.1%
54
 
0.1%
44
 
0.1%
273
 
< 0.1%
162
 
< 0.1%
Other values (20)24
 
0.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p3hli_he
Categorical

HIGH CARDINALITY

Distinct220
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size423.7 KiB
*
5250 
0
1203 
1
 
217
2
 
116
3
 
61
Other values (215)
620 

Length

Max length5
Median length1
Mean length1.084237311
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique132 ?
Unique (%)1.8%

Sample

1st row55266
2nd row499
3rd row328
4th row1
5th row1

Common Values

ValueCountFrequency (%)
*5250
70.3%
01203
 
16.1%
1217
 
2.9%
2116
 
1.6%
361
 
0.8%
442
 
0.6%
532
 
0.4%
631
 
0.4%
721
 
0.3%
819
 
0.3%
Other values (210)475
 
6.4%

Length

2022-11-06T21:07:51.700714image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
01203
 
16.1%
1217
 
2.9%
2116
 
1.6%
361
 
0.8%
442
 
0.6%
532
 
0.4%
631
 
0.4%
721
 
0.3%
819
 
0.3%
Other values (210)475
 
6.4%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p3hli_he_m
Categorical

HIGH CARDINALITY

Distinct171
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size423.5 KiB
*
5250 
0
1301 
1
 
231
2
 
102
3
 
49
Other values (166)
534 

Length

Max length5
Median length1
Mean length1.064684612
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique95 ?
Unique (%)1.3%

Sample

1st row30586
2nd row305
3rd row233
4th row1
5th row1

Common Values

ValueCountFrequency (%)
*5250
70.3%
01301
 
17.4%
1231
 
3.1%
2102
 
1.4%
349
 
0.7%
441
 
0.5%
537
 
0.5%
625
 
0.3%
719
 
0.3%
1318
 
0.2%
Other values (161)394
 
5.3%

Length

2022-11-06T21:07:51.952718image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
01301
 
17.4%
1231
 
3.1%
2102
 
1.4%
349
 
0.7%
441
 
0.5%
537
 
0.5%
625
 
0.3%
719
 
0.3%
1318
 
0.2%
Other values (161)394
 
5.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p3hli_he_f
Categorical

HIGH CARDINALITY

Distinct150
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size423.5 KiB
*
5250 
0
1393 
1
 
219
2
 
76
3
 
54
Other values (145)
 
475

Length

Max length5
Median length1
Mean length1.057051025
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique83 ?
Unique (%)1.1%

Sample

1st row24680
2nd row194
3rd row95
4th row0
5th row0

Common Values

ValueCountFrequency (%)
*5250
70.3%
01393
 
18.7%
1219
 
2.9%
276
 
1.0%
354
 
0.7%
431
 
0.4%
526
 
0.3%
824
 
0.3%
622
 
0.3%
1016
 
0.2%
Other values (140)356
 
4.8%

Length

2022-11-06T21:07:52.219714image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
01393
 
18.7%
1219
 
2.9%
276
 
1.0%
354
 
0.7%
431
 
0.4%
526
 
0.3%
824
 
0.3%
622
 
0.3%
1016
 
0.2%
Other values (140)356
 
4.8%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p5_hli
Categorical

HIGH CARDINALITY

Distinct223
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size423.7 KiB
*
5250 
0
1136 
1
 
243
2
 
121
3
 
79
Other values (218)
638 

Length

Max length5
Median length1
Mean length1.087987143
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique125 ?
Unique (%)1.7%

Sample

1st row60310
2nd row544
3rd row350
4th row1
5th row1

Common Values

ValueCountFrequency (%)
*5250
70.3%
01136
 
15.2%
1243
 
3.3%
2121
 
1.6%
379
 
1.1%
439
 
0.5%
536
 
0.5%
629
 
0.4%
724
 
0.3%
819
 
0.3%
Other values (213)491
 
6.6%

Length

2022-11-06T21:07:52.484714image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
01136
 
15.2%
1243
 
3.3%
2121
 
1.6%
379
 
1.1%
439
 
0.5%
536
 
0.5%
629
 
0.4%
724
 
0.3%
819
 
0.3%
Other values (213)491
 
6.6%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p5_hli_nhe
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct39
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size423.1 KiB
*
5250 
0
2053 
1
 
68
2
 
20
3
 
15
Other values (34)
 
61

Length

Max length4
Median length1
Mean length1.005089059
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)0.3%

Sample

1st row1242
2nd row8
3rd row10
4th row0
5th row0

Common Values

ValueCountFrequency (%)
*5250
70.3%
02053
 
27.5%
168
 
0.9%
220
 
0.3%
315
 
0.2%
48
 
0.1%
58
 
0.1%
75
 
0.1%
64
 
0.1%
93
 
< 0.1%
Other values (29)33
 
0.4%

Length

2022-11-06T21:07:52.735714image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
02053
 
27.5%
168
 
0.9%
220
 
0.3%
315
 
0.2%
48
 
0.1%
58
 
0.1%
75
 
0.1%
64
 
0.1%
93
 
< 0.1%
Other values (29)33
 
0.4%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p5_hli_he
Categorical

HIGH CARDINALITY

Distinct213
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size423.7 KiB
*
5250 
0
1203 
1
 
218
2
 
116
3
 
63
Other values (208)
617 

Length

Max length5
Median length1
Mean length1.084237311
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique122 ?
Unique (%)1.6%

Sample

1st row54626
2nd row495
3rd row326
4th row1
5th row1

Common Values

ValueCountFrequency (%)
*5250
70.3%
01203
 
16.1%
1218
 
2.9%
2116
 
1.6%
363
 
0.8%
439
 
0.5%
532
 
0.4%
631
 
0.4%
722
 
0.3%
818
 
0.2%
Other values (203)475
 
6.4%

Length

2022-11-06T21:07:52.937716image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
01203
 
16.1%
1218
 
2.9%
2116
 
1.6%
363
 
0.8%
439
 
0.5%
532
 
0.4%
631
 
0.4%
722
 
0.3%
818
 
0.2%
Other values (203)475
 
6.4%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

phog_ind
Categorical

HIGH CARDINALITY

Distinct293
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Memory size423.9 KiB
*
5250 
0
1189 
4
 
65
3
 
60
1
 
57
Other values (288)
846 

Length

Max length6
Median length1
Mean length1.121467792
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique188 ?
Unique (%)2.5%

Sample

1st row123248
2nd row942
3rd row375
4th row4
5th row4

Common Values

ValueCountFrequency (%)
*5250
70.3%
01189
 
15.9%
465
 
0.9%
360
 
0.8%
157
 
0.8%
555
 
0.7%
252
 
0.7%
641
 
0.5%
929
 
0.4%
725
 
0.3%
Other values (283)644
 
8.6%

Length

2022-11-06T21:07:53.209717image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
01189
 
15.9%
465
 
0.9%
360
 
0.8%
157
 
0.8%
555
 
0.7%
252
 
0.7%
641
 
0.5%
929
 
0.4%
725
 
0.3%
Other values (283)644
 
8.6%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

pcon_lim
Categorical

HIGH CARDINALITY

Distinct218
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size423.9 KiB
*
5250 
0
555 
1
 
317
2
 
197
3
 
154
Other values (213)
994 

Length

Max length6
Median length1
Mean length1.113566359
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique133 ?
Unique (%)1.8%

Sample

1st row119866
2nd row870
3rd row428
4th row161
5th row115

Common Values

ValueCountFrequency (%)
*5250
70.3%
0555
 
7.4%
1317
 
4.2%
2197
 
2.6%
3154
 
2.1%
484
 
1.1%
560
 
0.8%
752
 
0.7%
648
 
0.6%
947
 
0.6%
Other values (208)703
 
9.4%

Length

2022-11-06T21:07:53.460713image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
0555
 
7.4%
1317
 
4.2%
2197
 
2.6%
3154
 
2.1%
484
 
1.1%
560
 
0.8%
752
 
0.7%
648
 
0.6%
947
 
0.6%
Other values (208)703
 
9.4%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

pclim_mot
Categorical

HIGH CARDINALITY

Distinct170
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size423.7 KiB
*
5250 
0
755 
1
 
353
2
 
193
3
 
113
Other values (165)
803 

Length

Max length5
Median length1
Mean length1.081692782
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique103 ?
Unique (%)1.4%

Sample

1st row64872
2nd row515
3rd row212
4th row100
5th row75

Common Values

ValueCountFrequency (%)
*5250
70.3%
0755
 
10.1%
1353
 
4.7%
2193
 
2.6%
3113
 
1.5%
479
 
1.1%
571
 
1.0%
654
 
0.7%
754
 
0.7%
1332
 
0.4%
Other values (160)513
 
6.9%

Length

2022-11-06T21:07:53.687714image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
0755
 
10.1%
1353
 
4.7%
2193
 
2.6%
3113
 
1.5%
479
 
1.1%
571
 
1.0%
654
 
0.7%
754
 
0.7%
1332
 
0.4%
Other values (160)513
 
6.9%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

pclim_vis
Categorical

HIGH CARDINALITY

Distinct135
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size423.4 KiB
*
5250 
0
1075 
1
 
318
2
 
168
3
 
102
Other values (130)
554 

Length

Max length5
Median length1
Mean length1.05062274
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique81 ?
Unique (%)1.1%

Sample

1st row36711
2nd row243
3rd row122
4th row41
5th row32

Common Values

ValueCountFrequency (%)
*5250
70.3%
01075
 
14.4%
1318
 
4.3%
2168
 
2.2%
3102
 
1.4%
461
 
0.8%
548
 
0.6%
743
 
0.6%
637
 
0.5%
832
 
0.4%
Other values (125)333
 
4.5%

Length

2022-11-06T21:07:53.898717image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
01075
 
14.4%
1318
 
4.3%
2168
 
2.2%
3102
 
1.4%
461
 
0.8%
548
 
0.6%
743
 
0.6%
637
 
0.5%
832
 
0.4%
Other values (125)333
 
4.5%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

pclim_leng
Categorical

HIGH CARDINALITY
HIGH CORRELATION
HIGH CORRELATION

Distinct78
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size423.2 KiB
*
5250 
0
1446 
1
 
278
2
 
135
3
 
79
Other values (73)
 
279

Length

Max length5
Median length1
Mean length1.02169546
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique44 ?
Unique (%)0.6%

Sample

1st row10536
2nd row55
3rd row39
4th row11
5th row9

Common Values

ValueCountFrequency (%)
*5250
70.3%
01446
 
19.4%
1278
 
3.7%
2135
 
1.8%
379
 
1.1%
452
 
0.7%
533
 
0.4%
820
 
0.3%
617
 
0.2%
717
 
0.2%
Other values (68)140
 
1.9%

Length

2022-11-06T21:07:54.078712image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
01446
 
19.4%
1278
 
3.7%
2135
 
1.8%
379
 
1.1%
452
 
0.7%
533
 
0.4%
820
 
0.3%
717
 
0.2%
617
 
0.2%
Other values (68)140
 
1.9%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

pclim_aud
Categorical

HIGH CARDINALITY
HIGH CORRELATION
HIGH CORRELATION

Distinct87
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size423.3 KiB
*
5250 
0
1361 
1
 
298
2
 
128
3
 
92
Other values (82)
 
338

Length

Max length5
Median length1
Mean length1.027320209
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique49 ?
Unique (%)0.7%

Sample

1st row11522
2nd row87
3rd row45
4th row25
5th row21

Common Values

ValueCountFrequency (%)
*5250
70.3%
01361
 
18.2%
1298
 
4.0%
2128
 
1.7%
392
 
1.2%
451
 
0.7%
535
 
0.5%
630
 
0.4%
721
 
0.3%
821
 
0.3%
Other values (77)180
 
2.4%

Length

2022-11-06T21:07:54.284714image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
01361
 
18.2%
1298
 
4.0%
2128
 
1.7%
392
 
1.2%
451
 
0.7%
535
 
0.5%
630
 
0.4%
721
 
0.3%
821
 
0.3%
Other values (77)180
 
2.4%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

pclim_mot2
Categorical

HIGH CARDINALITY
HIGH CORRELATION
HIGH CORRELATION

Distinct74
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size423.2 KiB
*
5250 
0
1616 
1
 
259
2
 
94
3
 
45
Other values (69)
 
203

Length

Max length4
Median length1
Mean length1.017811705
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique47 ?
Unique (%)0.6%

Sample

1st row7124
2nd row48
3rd row13
4th row15
5th row11

Common Values

ValueCountFrequency (%)
*5250
70.3%
01616
 
21.6%
1259
 
3.5%
294
 
1.3%
345
 
0.6%
428
 
0.4%
517
 
0.2%
615
 
0.2%
715
 
0.2%
811
 
0.1%
Other values (64)117
 
1.6%

Length

2022-11-06T21:07:54.500717image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
01616
 
21.6%
1259
 
3.5%
294
 
1.3%
345
 
0.6%
428
 
0.4%
517
 
0.2%
615
 
0.2%
715
 
0.2%
811
 
0.1%
Other values (64)117
 
1.6%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

pclim_men
Categorical

HIGH CARDINALITY
HIGH CORRELATION
HIGH CORRELATION

Distinct69
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size423.2 KiB
*
5250 
0
1693 
1
 
234
2
 
73
3
 
51
Other values (64)
 
166

Length

Max length4
Median length1
Mean length1.01499933
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique47 ?
Unique (%)0.6%

Sample

1st row6248
2nd row52
3rd row13
4th row7
5th row5

Common Values

ValueCountFrequency (%)
*5250
70.3%
01693
 
22.7%
1234
 
3.1%
273
 
1.0%
351
 
0.7%
428
 
0.4%
520
 
0.3%
613
 
0.2%
87
 
0.1%
77
 
0.1%
Other values (59)91
 
1.2%

Length

2022-11-06T21:07:54.853718image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
01693
 
22.7%
1234
 
3.1%
273
 
1.0%
351
 
0.7%
428
 
0.4%
520
 
0.3%
613
 
0.2%
87
 
0.1%
77
 
0.1%
Other values (59)91
 
1.2%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

pclim_men2
Categorical

HIGH CARDINALITY
HIGH CORRELATION
HIGH CORRELATION

Distinct89
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size423.3 KiB
*
5250 
0
1400 
1
 
317
2
 
117
3
 
72
Other values (84)
 
311

Length

Max length5
Median length1
Mean length1.026114906
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique55 ?
Unique (%)0.7%

Sample

1st row12400
2nd row78
3rd row48
4th row19
5th row11

Common Values

ValueCountFrequency (%)
*5250
70.3%
01400
 
18.7%
1317
 
4.2%
2117
 
1.6%
372
 
1.0%
443
 
0.6%
539
 
0.5%
630
 
0.4%
817
 
0.2%
717
 
0.2%
Other values (79)165
 
2.2%

Length

2022-11-06T21:07:55.277732image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
01400
 
18.7%
1317
 
4.2%
2117
 
1.6%
372
 
1.0%
443
 
0.6%
539
 
0.5%
630
 
0.4%
717
 
0.2%
817
 
0.2%
Other values (79)165
 
2.2%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

psin_lim
Categorical

HIGH CARDINALITY

Distinct688
Distinct (%)9.2%
Missing0
Missing (%)0.0%
Memory size426.0 KiB
*
5250 
9
 
61
8
 
60
7
 
59
11
 
58
Other values (683)
1979 

Length

Max length7
Median length1
Mean length1.401098165
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique439 ?
Unique (%)5.9%

Sample

1st row2509937
2nd row11566
3rd row8527
4th row2470
5th row1622

Common Values

ValueCountFrequency (%)
*5250
70.3%
961
 
0.8%
860
 
0.8%
759
 
0.8%
1158
 
0.8%
1356
 
0.7%
1056
 
0.7%
1250
 
0.7%
646
 
0.6%
1542
 
0.6%
Other values (678)1729
 
23.2%

Length

2022-11-06T21:07:55.471712image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
961
 
0.8%
860
 
0.8%
759
 
0.8%
1158
 
0.8%
1356
 
0.7%
1056
 
0.7%
1250
 
0.7%
646
 
0.6%
1542
 
0.6%
Other values (678)1729
 
23.2%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p3a5_noa
Categorical

HIGH CARDINALITY

Distinct164
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size423.6 KiB
*
5250 
0
701 
1
 
376
2
 
212
3
 
159
Other values (159)
769 

Length

Max length5
Median length1
Mean length1.072719968
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique101 ?
Unique (%)1.4%

Sample

1st row83536
2nd row389
3rd row212
4th row58
5th row38

Common Values

ValueCountFrequency (%)
*5250
70.3%
0701
 
9.4%
1376
 
5.0%
2212
 
2.8%
3159
 
2.1%
492
 
1.2%
580
 
1.1%
656
 
0.7%
749
 
0.7%
836
 
0.5%
Other values (154)456
 
6.1%

Length

2022-11-06T21:07:55.756713image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
0701
 
9.4%
1376
 
5.0%
2212
 
2.8%
3159
 
2.1%
492
 
1.2%
580
 
1.1%
656
 
0.7%
749
 
0.7%
836
 
0.5%
Other values (154)456
 
6.1%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p3a5_noa_m
Categorical

HIGH CARDINALITY

Distinct136
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size423.4 KiB
*
5250 
0
968 
1
 
374
2
 
213
3
 
113
Other values (131)
549 

Length

Max length5
Median length1
Mean length1.051426276
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique90 ?
Unique (%)1.2%

Sample

1st row43021
2nd row175
3rd row110
4th row34
5th row22

Common Values

ValueCountFrequency (%)
*5250
70.3%
0968
 
13.0%
1374
 
5.0%
2213
 
2.9%
3113
 
1.5%
487
 
1.2%
555
 
0.7%
638
 
0.5%
734
 
0.5%
1022
 
0.3%
Other values (126)313
 
4.2%

Length

2022-11-06T21:07:55.990717image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
0968
 
13.0%
1374
 
5.0%
2213
 
2.9%
3113
 
1.5%
487
 
1.2%
555
 
0.7%
638
 
0.5%
734
 
0.5%
1022
 
0.3%
Other values (126)313
 
4.2%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p3a5_noa_f
Categorical

HIGH CARDINALITY

Distinct131
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size423.4 KiB
*
5250 
0
987 
1
 
409
2
 
190
3
 
124
Other values (126)
 
507

Length

Max length5
Median length1
Mean length1.049283514
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique87 ?
Unique (%)1.2%

Sample

1st row40515
2nd row214
3rd row102
4th row24
5th row16

Common Values

ValueCountFrequency (%)
*5250
70.3%
0987
 
13.2%
1409
 
5.5%
2190
 
2.5%
3124
 
1.7%
481
 
1.1%
541
 
0.5%
640
 
0.5%
728
 
0.4%
1125
 
0.3%
Other values (121)292
 
3.9%

Length

2022-11-06T21:07:56.198713image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
0987
 
13.2%
1409
 
5.5%
2190
 
2.5%
3124
 
1.7%
481
 
1.1%
541
 
0.5%
640
 
0.5%
728
 
0.4%
1125
 
0.3%
Other values (121)292
 
3.9%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p6a11_noa
Categorical

HIGH CARDINALITY
HIGH CORRELATION
HIGH CORRELATION

Distinct70
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size423.2 KiB
*
5250 
0
1482 
1
 
307
2
 
134
3
 
67
Other values (65)
 
227

Length

Max length4
Median length1
Mean length1.016874247
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique44 ?
Unique (%)0.6%

Sample

1st row7388
2nd row98
3rd row50
4th row6
5th row3

Common Values

ValueCountFrequency (%)
*5250
70.3%
01482
 
19.8%
1307
 
4.1%
2134
 
1.8%
367
 
0.9%
451
 
0.7%
528
 
0.4%
619
 
0.3%
714
 
0.2%
811
 
0.1%
Other values (60)104
 
1.4%

Length

2022-11-06T21:07:56.400714image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
01482
 
19.8%
1307
 
4.1%
2134
 
1.8%
367
 
0.9%
451
 
0.7%
528
 
0.4%
619
 
0.3%
714
 
0.2%
811
 
0.1%
Other values (60)104
 
1.4%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p6a11_noam
Categorical

HIGH CARDINALITY
HIGH CORRELATION
HIGH CORRELATION

Distinct60
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size423.1 KiB
*
5250 
0
1671 
1
 
260
2
 
105
3
 
46
Other values (55)
 
135

Length

Max length4
Median length1
Mean length1.011249498
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique37 ?
Unique (%)0.5%

Sample

1st row4024
2nd row60
3rd row24
4th row4
5th row3

Common Values

ValueCountFrequency (%)
*5250
70.3%
01671
 
22.4%
1260
 
3.5%
2105
 
1.4%
346
 
0.6%
427
 
0.4%
515
 
0.2%
610
 
0.1%
79
 
0.1%
87
 
0.1%
Other values (50)67
 
0.9%

Length

2022-11-06T21:07:56.608715image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
01671
 
22.4%
1260
 
3.5%
2105
 
1.4%
346
 
0.6%
427
 
0.4%
515
 
0.2%
610
 
0.1%
79
 
0.1%
87
 
0.1%
Other values (50)67
 
0.9%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p6a11_noaf
Categorical

HIGH CARDINALITY
HIGH CORRELATION
HIGH CORRELATION

Distinct58
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size423.1 KiB
*
5250 
0
1691 
1
 
274
2
 
91
3
 
41
Other values (53)
 
120

Length

Max length4
Median length1
Mean length1.01031204
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique37 ?
Unique (%)0.5%

Sample

1st row3364
2nd row38
3rd row26
4th row2
5th row0

Common Values

ValueCountFrequency (%)
*5250
70.3%
01691
 
22.6%
1274
 
3.7%
291
 
1.2%
341
 
0.5%
423
 
0.3%
511
 
0.1%
710
 
0.1%
97
 
0.1%
65
 
0.1%
Other values (48)64
 
0.9%

Length

2022-11-06T21:07:56.791715image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
01691
 
22.6%
1274
 
3.7%
291
 
1.2%
341
 
0.5%
423
 
0.3%
511
 
0.1%
710
 
0.1%
97
 
0.1%
65
 
0.1%
Other values (48)64
 
0.9%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p12a14noa
Categorical

HIGH CARDINALITY
HIGH CORRELATION
HIGH CORRELATION

Distinct79
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size423.2 KiB
*
5250 
0
1460 
1
 
283
2
 
144
3
 
79
Other values (74)
 
251

Length

Max length4
Median length1
Mean length1.019686621
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique48 ?
Unique (%)0.6%

Sample

1st row8545
2nd row95
3rd row38
4th row13
5th row10

Common Values

ValueCountFrequency (%)
*5250
70.3%
01460
 
19.6%
1283
 
3.8%
2144
 
1.9%
379
 
1.1%
450
 
0.7%
524
 
0.3%
721
 
0.3%
619
 
0.3%
1011
 
0.1%
Other values (69)126
 
1.7%

Length

2022-11-06T21:07:56.956717image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
01460
 
19.6%
1283
 
3.8%
2144
 
1.9%
379
 
1.1%
450
 
0.7%
524
 
0.3%
721
 
0.3%
619
 
0.3%
1011
 
0.1%
Other values (69)126
 
1.7%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p12a14noam
Categorical

HIGH CARDINALITY
HIGH CORRELATION
HIGH CORRELATION

Distinct65
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size423.2 KiB
*
5250 
0
1616 
1
 
260
2
 
99
3
 
73
Other values (60)
 
169

Length

Max length4
Median length1
Mean length1.01392795
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique38 ?
Unique (%)0.5%

Sample

1st row5014
2nd row61
3rd row25
4th row10
5th row7

Common Values

ValueCountFrequency (%)
*5250
70.3%
01616
 
21.6%
1260
 
3.5%
299
 
1.3%
373
 
1.0%
430
 
0.4%
519
 
0.3%
612
 
0.2%
811
 
0.1%
710
 
0.1%
Other values (55)87
 
1.2%

Length

2022-11-06T21:07:57.146717image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
01616
 
21.6%
1260
 
3.5%
299
 
1.3%
373
 
1.0%
430
 
0.4%
519
 
0.3%
612
 
0.2%
811
 
0.1%
710
 
0.1%
Other values (55)87
 
1.2%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p12a14noaf
Categorical

HIGH CARDINALITY
HIGH CORRELATION
HIGH CORRELATION

Distinct58
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size423.1 KiB
*
5250 
0
1708 
1
 
249
2
 
98
3
 
36
Other values (53)
 
126

Length

Max length4
Median length1
Mean length1.011785188
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique35 ?
Unique (%)0.5%

Sample

1st row3531
2nd row34
3rd row13
4th row3
5th row3

Common Values

ValueCountFrequency (%)
*5250
70.3%
01708
 
22.9%
1249
 
3.3%
298
 
1.3%
336
 
0.5%
417
 
0.2%
616
 
0.2%
513
 
0.2%
78
 
0.1%
125
 
0.1%
Other values (48)67
 
0.9%

Length

2022-11-06T21:07:57.318714image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
01708
 
22.9%
1249
 
3.3%
298
 
1.3%
336
 
0.5%
417
 
0.2%
616
 
0.2%
513
 
0.2%
78
 
0.1%
125
 
0.1%
Other values (48)67
 
0.9%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p15a17a
Categorical

HIGH CARDINALITY

Distinct184
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size423.7 KiB
*
5250 
0
834 
1
 
316
2
 
170
3
 
87
Other values (179)
810 

Length

Max length6
Median length1
Mean length1.090129905
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique110 ?
Unique (%)1.5%

Sample

1st row111957
2nd row272
3rd row224
4th row100
5th row73

Common Values

ValueCountFrequency (%)
*5250
70.3%
0834
 
11.2%
1316
 
4.2%
2170
 
2.3%
387
 
1.2%
562
 
0.8%
754
 
0.7%
453
 
0.7%
646
 
0.6%
838
 
0.5%
Other values (174)557
 
7.5%

Length

2022-11-06T21:07:57.488713image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
0834
 
11.2%
1316
 
4.2%
2170
 
2.3%
387
 
1.2%
562
 
0.8%
754
 
0.7%
453
 
0.7%
646
 
0.6%
838
 
0.5%
Other values (174)557
 
7.5%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p15a17a_m
Categorical

HIGH CARDINALITY

Distinct144
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size423.5 KiB
*
5250 
0
1057 
1
 
286
2
 
158
3
 
91
Other values (139)
625 

Length

Max length5
Median length1
Mean length1.06093478
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique92 ?
Unique (%)1.2%

Sample

1st row55951
2nd row144
3rd row164
4th row53
5th row38

Common Values

ValueCountFrequency (%)
*5250
70.3%
01057
 
14.2%
1286
 
3.8%
2158
 
2.1%
391
 
1.2%
475
 
1.0%
564
 
0.9%
639
 
0.5%
839
 
0.5%
732
 
0.4%
Other values (134)376
 
5.0%

Length

2022-11-06T21:07:57.687716image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
01057
 
14.2%
1286
 
3.8%
2158
 
2.1%
391
 
1.2%
475
 
1.0%
564
 
0.9%
639
 
0.5%
839
 
0.5%
732
 
0.4%
Other values (134)376
 
5.0%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p15a17a_f
Categorical

HIGH CARDINALITY

Distinct139
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size423.5 KiB
*
5250 
0
1059 
1
 
308
2
 
143
3
 
90
Other values (134)
617 

Length

Max length5
Median length1
Mean length1.060399089
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique81 ?
Unique (%)1.1%

Sample

1st row56006
2nd row128
3rd row60
4th row47
5th row35

Common Values

ValueCountFrequency (%)
*5250
70.3%
01059
 
14.2%
1308
 
4.1%
2143
 
1.9%
390
 
1.2%
484
 
1.1%
548
 
0.6%
743
 
0.6%
641
 
0.5%
828
 
0.4%
Other values (129)373
 
5.0%

Length

2022-11-06T21:07:57.921716image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
01059
 
14.2%
1308
 
4.1%
2143
 
1.9%
390
 
1.2%
484
 
1.1%
548
 
0.6%
743
 
0.6%
641
 
0.5%
828
 
0.4%
Other values (129)373
 
5.0%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p18a24a
Categorical

HIGH CARDINALITY

Distinct162
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size423.6 KiB
*
5250 
0
1077 
1
 
301
2
 
131
3
 
86
Other values (157)
622 

Length

Max length6
Median length1
Mean length1.067898755
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique103 ?
Unique (%)1.4%

Sample

1st row107543
2nd row163
3rd row345
4th row58
5th row44

Common Values

ValueCountFrequency (%)
*5250
70.3%
01077
 
14.4%
1301
 
4.0%
2131
 
1.8%
386
 
1.2%
464
 
0.9%
557
 
0.8%
639
 
0.5%
828
 
0.4%
728
 
0.4%
Other values (152)406
 
5.4%

Length

2022-11-06T21:07:58.115712image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
01077
 
14.4%
1301
 
4.0%
2131
 
1.8%
386
 
1.2%
464
 
0.9%
557
 
0.8%
639
 
0.5%
828
 
0.4%
728
 
0.4%
Other values (152)406
 
5.4%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p18a24a_m
Categorical

HIGH CARDINALITY

Distinct126
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size423.4 KiB
*
5250 
0
1285 
1
 
278
2
 
111
3
 
95
Other values (121)
 
448

Length

Max length5
Median length1
Mean length1.046605062
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique84 ?
Unique (%)1.1%

Sample

1st row55228
2nd row77
3rd row298
4th row28
5th row22

Common Values

ValueCountFrequency (%)
*5250
70.3%
01285
 
17.2%
1278
 
3.7%
2111
 
1.5%
395
 
1.3%
455
 
0.7%
533
 
0.4%
1129
 
0.4%
629
 
0.4%
827
 
0.4%
Other values (116)275
 
3.7%

Length

2022-11-06T21:07:58.304716image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
01285
 
17.2%
1278
 
3.7%
2111
 
1.5%
395
 
1.3%
455
 
0.7%
533
 
0.4%
1129
 
0.4%
629
 
0.4%
827
 
0.4%
Other values (116)275
 
3.7%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p18a24a_f
Categorical

HIGH CARDINALITY

Distinct122
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size423.4 KiB
*
5250 
0
1284 
1
 
271
2
 
133
3
 
70
Other values (117)
 
459

Length

Max length5
Median length1
Mean length1.044328378
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique77 ?
Unique (%)1.0%

Sample

1st row52315
2nd row86
3rd row47
4th row30
5th row22

Common Values

ValueCountFrequency (%)
*5250
70.3%
01284
 
17.2%
1271
 
3.6%
2133
 
1.8%
370
 
0.9%
452
 
0.7%
741
 
0.5%
536
 
0.5%
634
 
0.5%
1024
 
0.3%
Other values (112)272
 
3.6%

Length

2022-11-06T21:07:58.500714image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
01284
 
17.2%
1271
 
3.6%
2133
 
1.8%
370
 
0.9%
452
 
0.7%
741
 
0.5%
536
 
0.5%
634
 
0.5%
1024
 
0.3%
Other values (112)272
 
3.6%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p8a14an
Categorical

HIGH CARDINALITY
HIGH CORRELATION
HIGH CORRELATION

Distinct82
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size423.2 KiB
*
5250 
0
1394 
1
 
324
2
 
137
3
 
79
Other values (77)
 
283

Length

Max length4
Median length1
Mean length1.019954466
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique54 ?
Unique (%)0.7%

Sample

1st row7757
2nd row78
3rd row33
4th row16
5th row12

Common Values

ValueCountFrequency (%)
*5250
70.3%
01394
 
18.7%
1324
 
4.3%
2137
 
1.8%
379
 
1.1%
452
 
0.7%
538
 
0.5%
723
 
0.3%
623
 
0.3%
916
 
0.2%
Other values (72)131
 
1.8%

Length

2022-11-06T21:07:58.735716image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
01394
 
18.7%
1324
 
4.3%
2137
 
1.8%
379
 
1.1%
452
 
0.7%
538
 
0.5%
623
 
0.3%
723
 
0.3%
916
 
0.2%
Other values (72)131
 
1.8%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p8a14an_m
Categorical

HIGH CARDINALITY
HIGH CORRELATION
HIGH CORRELATION

Distinct62
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size423.2 KiB
*
5250 
0
1539 
1
 
298
2
 
126
3
 
60
Other values (57)
 
194

Length

Max length4
Median length1
Mean length1.01499933
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique36 ?
Unique (%)0.5%

Sample

1st row4785
2nd row54
3rd row18
4th row14
5th row10

Common Values

ValueCountFrequency (%)
*5250
70.3%
01539
 
20.6%
1298
 
4.0%
2126
 
1.7%
360
 
0.8%
436
 
0.5%
523
 
0.3%
615
 
0.2%
712
 
0.2%
912
 
0.2%
Other values (52)96
 
1.3%

Length

2022-11-06T21:07:59.188714image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
01539
 
20.6%
1298
 
4.0%
2126
 
1.7%
360
 
0.8%
436
 
0.5%
523
 
0.3%
615
 
0.2%
712
 
0.2%
912
 
0.2%
Other values (52)96
 
1.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p8a14an_f
Categorical

HIGH CARDINALITY
HIGH CORRELATION
HIGH CORRELATION

Distinct56
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size423.1 KiB
*
5250 
0
1684 
1
 
255
2
 
102
3
 
47
Other values (51)
 
129

Length

Max length4
Median length1
Mean length1.010579885
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique34 ?
Unique (%)0.5%

Sample

1st row2972
2nd row24
3rd row15
4th row2
5th row2

Common Values

ValueCountFrequency (%)
*5250
70.3%
01684
 
22.6%
1255
 
3.4%
2102
 
1.4%
347
 
0.6%
424
 
0.3%
516
 
0.2%
99
 
0.1%
68
 
0.1%
88
 
0.1%
Other values (46)64
 
0.9%

Length

2022-11-06T21:07:59.512713image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
01684
 
22.6%
1255
 
3.4%
2102
 
1.4%
347
 
0.6%
424
 
0.3%
516
 
0.2%
99
 
0.1%
88
 
0.1%
68
 
0.1%
Other values (46)64
 
0.9%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p15ym_an
Categorical

HIGH CARDINALITY

Distinct182
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size423.9 KiB
*
5250 
0
 
497
1
 
286
2
 
223
3
 
140
Other values (177)
1071 

Length

Max length5
Median length1
Mean length1.112494978
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique98 ?
Unique (%)1.3%

Sample

1st row56899
2nd row939
3rd row459
4th row76
5th row37

Common Values

ValueCountFrequency (%)
*5250
70.3%
0497
 
6.7%
1286
 
3.8%
2223
 
3.0%
3140
 
1.9%
494
 
1.3%
569
 
0.9%
754
 
0.7%
852
 
0.7%
650
 
0.7%
Other values (172)752
 
10.1%

Length

2022-11-06T21:07:59.971721image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
0497
 
6.7%
1286
 
3.8%
2223
 
3.0%
3140
 
1.9%
494
 
1.3%
569
 
0.9%
754
 
0.7%
852
 
0.7%
650
 
0.7%
Other values (172)752
 
10.1%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p15ym_an_m
Categorical

HIGH CARDINALITY

Distinct137
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size423.6 KiB
*
5250 
0
649 
1
 
364
2
 
210
3
 
148
Other values (132)
846 

Length

Max length5
Median length1
Mean length1.07593411
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique74 ?
Unique (%)1.0%

Sample

1st row28751
2nd row611
3rd row313
4th row49
5th row24

Common Values

ValueCountFrequency (%)
*5250
70.3%
0649
 
8.7%
1364
 
4.9%
2210
 
2.8%
3148
 
2.0%
494
 
1.3%
585
 
1.1%
652
 
0.7%
849
 
0.7%
747
 
0.6%
Other values (127)519
 
7.0%

Length

2022-11-06T21:08:00.273715image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
0649
 
8.7%
1364
 
4.9%
2210
 
2.8%
3148
 
2.0%
494
 
1.3%
585
 
1.1%
652
 
0.7%
849
 
0.7%
747
 
0.6%
Other values (127)519
 
7.0%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p15ym_an_f
Categorical

HIGH CARDINALITY

Distinct133
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size423.5 KiB
*
5250 
0
791 
1
 
360
2
 
161
3
 
122
Other values (128)
783 

Length

Max length5
Median length1
Mean length1.066961296
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique78 ?
Unique (%)1.0%

Sample

1st row28148
2nd row328
3rd row146
4th row27
5th row13

Common Values

ValueCountFrequency (%)
*5250
70.3%
0791
 
10.6%
1360
 
4.8%
2161
 
2.2%
3122
 
1.6%
488
 
1.2%
574
 
1.0%
667
 
0.9%
755
 
0.7%
841
 
0.5%
Other values (123)458
 
6.1%

Length

2022-11-06T21:08:00.521716image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
0791
 
10.6%
1360
 
4.8%
2161
 
2.2%
3122
 
1.6%
488
 
1.2%
574
 
1.0%
667
 
0.9%
755
 
0.7%
841
 
0.5%
Other values (123)458
 
6.1%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p15ym_se
Categorical

HIGH CARDINALITY

Distinct192
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size423.9 KiB
*
5250 
0
 
445
1
 
309
2
 
211
3
 
143
Other values (187)
1109 

Length

Max length5
Median length1
Mean length1.113968126
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique116 ?
Unique (%)1.6%

Sample

1st row69529
2nd row1168
3rd row513
4th row73
5th row37

Common Values

ValueCountFrequency (%)
*5250
70.3%
0445
 
6.0%
1309
 
4.1%
2211
 
2.8%
3143
 
1.9%
492
 
1.2%
578
 
1.0%
670
 
0.9%
756
 
0.7%
954
 
0.7%
Other values (182)759
 
10.2%

Length

2022-11-06T21:08:00.736717image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
0445
 
6.0%
1309
 
4.1%
2211
 
2.8%
3143
 
1.9%
492
 
1.2%
578
 
1.0%
670
 
0.9%
756
 
0.7%
954
 
0.7%
Other values (182)759
 
10.2%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p15ym_se_m
Categorical

HIGH CARDINALITY

Distinct143
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size423.6 KiB
*
5250 
0
590 
1
 
388
2
 
197
3
 
151
Other values (138)
891 

Length

Max length5
Median length1
Mean length1.078880407
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique80 ?
Unique (%)1.1%

Sample

1st row35978
2nd row781
3rd row355
4th row43
5th row22

Common Values

ValueCountFrequency (%)
*5250
70.3%
0590
 
7.9%
1388
 
5.2%
2197
 
2.6%
3151
 
2.0%
4102
 
1.4%
581
 
1.1%
664
 
0.9%
852
 
0.7%
746
 
0.6%
Other values (133)546
 
7.3%

Length

2022-11-06T21:08:00.963717image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
0590
 
7.9%
1388
 
5.2%
2197
 
2.6%
3151
 
2.0%
4102
 
1.4%
581
 
1.1%
664
 
0.9%
852
 
0.7%
746
 
0.6%
Other values (133)546
 
7.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p15ym_se_f
Categorical

HIGH CARDINALITY

Distinct138
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size423.6 KiB
*
5250 
0
763 
1
 
358
2
 
190
3
 
127
Other values (133)
779 

Length

Max length5
Median length1
Mean length1.068032677
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique82 ?
Unique (%)1.1%

Sample

1st row33551
2nd row387
3rd row158
4th row30
5th row15

Common Values

ValueCountFrequency (%)
*5250
70.3%
0763
 
10.2%
1358
 
4.8%
2190
 
2.5%
3127
 
1.7%
495
 
1.3%
573
 
1.0%
758
 
0.8%
657
 
0.8%
841
 
0.5%
Other values (128)455
 
6.1%

Length

2022-11-06T21:08:01.154715image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
0763
 
10.2%
1358
 
4.8%
2190
 
2.5%
3127
 
1.7%
495
 
1.3%
573
 
1.0%
758
 
0.8%
657
 
0.8%
841
 
0.5%
Other values (128)455
 
6.1%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p15pri_in
Categorical

HIGH CARDINALITY

Distinct309
Distinct (%)4.1%
Missing0
Missing (%)0.0%
Memory size424.5 KiB
*
5250 
2
 
197
1
 
188
3
 
163
0
 
129
Other values (304)
1540 

Length

Max length6
Median length1
Mean length1.192312843
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique167 ?
Unique (%)2.2%

Sample

1st row199642
2nd row2908
3rd row1452
4th row370
5th row212

Common Values

ValueCountFrequency (%)
*5250
70.3%
2197
 
2.6%
1188
 
2.5%
3163
 
2.2%
0129
 
1.7%
4121
 
1.6%
596
 
1.3%
771
 
1.0%
671
 
1.0%
952
 
0.7%
Other values (299)1129
 
15.1%

Length

2022-11-06T21:08:01.514712image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
2197
 
2.6%
1188
 
2.5%
3163
 
2.2%
0129
 
1.7%
4121
 
1.6%
596
 
1.3%
771
 
1.0%
671
 
1.0%
952
 
0.7%
Other values (299)1129
 
15.1%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p15pri_inm
Categorical

HIGH CARDINALITY

Distinct238
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size424.1 KiB
*
5250 
1
 
299
0
 
238
2
 
229
3
 
160
Other values (233)
1291 

Length

Max length6
Median length1
Mean length1.148520155
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique133 ?
Unique (%)1.8%

Sample

1st row103084
2nd row1917
3rd row1060
4th row223
5th row134

Common Values

ValueCountFrequency (%)
*5250
70.3%
1299
 
4.0%
0238
 
3.2%
2229
 
3.1%
3160
 
2.1%
4110
 
1.5%
582
 
1.1%
661
 
0.8%
757
 
0.8%
945
 
0.6%
Other values (228)936
 
12.5%

Length

2022-11-06T21:08:01.726716image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
1299
 
4.0%
0238
 
3.2%
2229
 
3.1%
3160
 
2.1%
4110
 
1.5%
582
 
1.1%
661
 
0.8%
757
 
0.8%
945
 
0.6%
Other values (228)936
 
12.5%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p15pri_inf
Categorical

HIGH CARDINALITY

Distinct219
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size424.0 KiB
*
5250 
1
 
357
0
 
350
2
 
214
3
 
148
Other values (214)
1148 

Length

Max length5
Median length1
Mean length1.129235302
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique122 ?
Unique (%)1.6%

Sample

1st row96558
2nd row991
3rd row392
4th row147
5th row78

Common Values

ValueCountFrequency (%)
*5250
70.3%
1357
 
4.8%
0350
 
4.7%
2214
 
2.9%
3148
 
2.0%
492
 
1.2%
576
 
1.0%
662
 
0.8%
762
 
0.8%
1039
 
0.5%
Other values (209)817
 
10.9%

Length

2022-11-06T21:08:01.934713image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
1357
 
4.8%
0350
 
4.7%
2214
 
2.9%
3148
 
2.0%
492
 
1.2%
576
 
1.0%
662
 
0.8%
762
 
0.8%
1039
 
0.5%
Other values (209)817
 
10.9%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p15pri_co
Categorical

HIGH CARDINALITY

Distinct292
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Memory size424.3 KiB
*
5250 
2
 
244
1
 
229
0
 
183
3
 
179
Other values (287)
1382 

Length

Max length6
Median length1
Mean length1.171286996
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique161 ?
Unique (%)2.2%

Sample

1st row232766
2nd row1992
3rd row1164
4th row374
5th row265

Common Values

ValueCountFrequency (%)
*5250
70.3%
2244
 
3.3%
1229
 
3.1%
0183
 
2.5%
3179
 
2.4%
4116
 
1.6%
586
 
1.2%
773
 
1.0%
655
 
0.7%
848
 
0.6%
Other values (282)1004
 
13.4%

Length

2022-11-06T21:08:02.113732image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
2244
 
3.3%
1229
 
3.1%
0183
 
2.5%
3179
 
2.4%
4116
 
1.6%
586
 
1.2%
773
 
1.0%
655
 
0.7%
848
 
0.6%
Other values (282)1004
 
13.4%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p15pri_com
Categorical

HIGH CARDINALITY

Distinct232
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size424.0 KiB
*
5250 
1
 
372
0
 
344
2
 
231
3
 
141
Other values (227)
1129 

Length

Max length6
Median length1
Mean length1.129101379
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique140 ?
Unique (%)1.9%

Sample

1st row114252
2nd row1221
3rd row813
4th row198
5th row140

Common Values

ValueCountFrequency (%)
*5250
70.3%
1372
 
5.0%
0344
 
4.6%
2231
 
3.1%
3141
 
1.9%
4107
 
1.4%
667
 
0.9%
566
 
0.9%
750
 
0.7%
842
 
0.6%
Other values (222)797
 
10.7%

Length

2022-11-06T21:08:02.296737image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
1372
 
5.0%
0344
 
4.6%
2231
 
3.1%
3141
 
1.9%
4107
 
1.4%
667
 
0.9%
566
 
0.9%
750
 
0.7%
842
 
0.6%
Other values (222)797
 
10.7%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p15pri_cof
Categorical

HIGH CARDINALITY

Distinct219
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size423.9 KiB
*
5250 
0
 
411
1
 
383
2
 
228
3
 
158
Other values (214)
1037 

Length

Max length6
Median length1
Mean length1.116378733
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique128 ?
Unique (%)1.7%

Sample

1st row118514
2nd row771
3rd row351
4th row176
5th row125

Common Values

ValueCountFrequency (%)
*5250
70.3%
0411
 
5.5%
1383
 
5.1%
2228
 
3.1%
3158
 
2.1%
495
 
1.3%
566
 
0.9%
654
 
0.7%
752
 
0.7%
941
 
0.5%
Other values (209)729
 
9.8%

Length

2022-11-06T21:08:02.466791image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
0411
 
5.5%
1383
 
5.1%
2228
 
3.1%
3158
 
2.1%
495
 
1.3%
566
 
0.9%
654
 
0.7%
752
 
0.7%
941
 
0.5%
Other values (209)729
 
9.8%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p15sec_in
Categorical

HIGH CARDINALITY

Distinct202
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size423.8 KiB
*
5250 
0
559 
1
 
382
2
 
192
3
 
116
Other values (197)
968 

Length

Max length6
Median length1
Mean length1.106602384
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique126 ?
Unique (%)1.7%

Sample

1st row111805
2nd row584
3rd row877
4th row127
5th row85

Common Values

ValueCountFrequency (%)
*5250
70.3%
0559
 
7.5%
1382
 
5.1%
2192
 
2.6%
3116
 
1.6%
484
 
1.1%
568
 
0.9%
660
 
0.8%
745
 
0.6%
842
 
0.6%
Other values (192)669
 
9.0%

Length

2022-11-06T21:08:02.666791image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
0559
 
7.5%
1382
 
5.1%
2192
 
2.6%
3116
 
1.6%
484
 
1.1%
568
 
0.9%
660
 
0.8%
745
 
0.6%
842
 
0.6%
Other values (192)669
 
9.0%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p15sec_inm
Categorical

HIGH CARDINALITY

Distinct163
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size423.6 KiB
*
5250 
0
751 
1
 
364
2
 
198
3
 
108
Other values (158)
796 

Length

Max length5
Median length1
Mean length1.077005491
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique93 ?
Unique (%)1.2%

Sample

1st row62337
2nd row379
3rd row744
4th row69
5th row47

Common Values

ValueCountFrequency (%)
*5250
70.3%
0751
 
10.1%
1364
 
4.9%
2198
 
2.7%
3108
 
1.4%
489
 
1.2%
571
 
1.0%
661
 
0.8%
946
 
0.6%
738
 
0.5%
Other values (153)491
 
6.6%

Length

2022-11-06T21:08:02.868788image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
0751
 
10.1%
1364
 
4.9%
2198
 
2.7%
3108
 
1.4%
489
 
1.2%
571
 
1.0%
661
 
0.8%
946
 
0.6%
738
 
0.5%
Other values (153)491
 
6.6%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p15sec_inf
Categorical

HIGH CARDINALITY

Distinct143
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size423.5 KiB
*
5250 
0
912 
1
 
371
2
 
152
3
 
114
Other values (138)
668 

Length

Max length5
Median length1
Mean length1.062274006
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique85 ?
Unique (%)1.1%

Sample

1st row49468
2nd row205
3rd row133
4th row58
5th row38

Common Values

ValueCountFrequency (%)
*5250
70.3%
0912
 
12.2%
1371
 
5.0%
2152
 
2.0%
3114
 
1.5%
478
 
1.0%
562
 
0.8%
660
 
0.8%
846
 
0.6%
734
 
0.5%
Other values (133)388
 
5.2%

Length

2022-11-06T21:08:03.049788image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
0912
 
12.2%
1371
 
5.0%
2152
 
2.0%
3114
 
1.5%
478
 
1.0%
562
 
0.8%
660
 
0.8%
846
 
0.6%
734
 
0.5%
Other values (133)388
 
5.2%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p15sec_co
Categorical

HIGH CARDINALITY

Distinct350
Distinct (%)4.7%
Missing0
Missing (%)0.0%
Memory size424.4 KiB
*
5250 
1
 
237
2
 
226
0
 
217
3
 
167
Other values (345)
1370 

Length

Max length6
Median length1
Mean length1.189634391
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique202 ?
Unique (%)2.7%

Sample

1st row454577
2nd row1729
3rd row2381
4th row497
5th row337

Common Values

ValueCountFrequency (%)
*5250
70.3%
1237
 
3.2%
2226
 
3.0%
0217
 
2.9%
3167
 
2.2%
4120
 
1.6%
588
 
1.2%
652
 
0.7%
841
 
0.5%
739
 
0.5%
Other values (340)1030
 
13.8%

Length

2022-11-06T21:08:03.235787image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
1237
 
3.2%
2226
 
3.0%
0217
 
2.9%
3167
 
2.2%
4120
 
1.6%
588
 
1.2%
652
 
0.7%
841
 
0.5%
739
 
0.5%
Other values (340)1030
 
13.8%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p15sec_com
Categorical

HIGH CARDINALITY

Distinct269
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size424.1 KiB
*
5250 
0
 
406
1
 
338
2
 
239
3
 
122
Other values (264)
1112 

Length

Max length6
Median length1
Mean length1.145439936
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique151 ?
Unique (%)2.0%

Sample

1st row226167
2nd row965
3rd row1971
4th row281
5th row190

Common Values

ValueCountFrequency (%)
*5250
70.3%
0406
 
5.4%
1338
 
4.5%
2239
 
3.2%
3122
 
1.6%
490
 
1.2%
563
 
0.8%
942
 
0.6%
640
 
0.5%
738
 
0.5%
Other values (259)839
 
11.2%

Length

2022-11-06T21:08:03.393788image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
0406
 
5.4%
1338
 
4.5%
2239
 
3.2%
3122
 
1.6%
490
 
1.2%
563
 
0.8%
942
 
0.6%
640
 
0.5%
738
 
0.5%
Other values (259)839
 
11.2%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p15sec_cof
Categorical

HIGH CARDINALITY

Distinct268
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size424.1 KiB
*
5250 
0
 
419
1
 
368
2
 
225
3
 
132
Other values (263)
1073 

Length

Max length6
Median length1
Mean length1.141556181
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique165 ?
Unique (%)2.2%

Sample

1st row228410
2nd row764
3rd row410
4th row216
5th row147

Common Values

ValueCountFrequency (%)
*5250
70.3%
0419
 
5.6%
1368
 
4.9%
2225
 
3.0%
3132
 
1.8%
475
 
1.0%
556
 
0.7%
742
 
0.6%
640
 
0.5%
833
 
0.4%
Other values (258)827
 
11.1%

Length

2022-11-06T21:08:03.557789image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
0419
 
5.6%
1368
 
4.9%
2225
 
3.0%
3132
 
1.8%
475
 
1.0%
556
 
0.7%
742
 
0.6%
640
 
0.5%
833
 
0.4%
Other values (258)827
 
11.1%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p18ym_pb
Categorical

HIGH CARDINALITY

Distinct309
Distinct (%)4.1%
Missing0
Missing (%)0.0%
Memory size424.2 KiB
*
5250 
0
 
460
1
 
274
2
 
172
3
 
138
Other values (304)
1173 

Length

Max length6
Median length1
Mean length1.156287666
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique191 ?
Unique (%)2.6%

Sample

1st row722087
2nd row1232
3rd row1042
4th row391
5th row283

Common Values

ValueCountFrequency (%)
*5250
70.3%
0460
 
6.2%
1274
 
3.7%
2172
 
2.3%
3138
 
1.8%
496
 
1.3%
588
 
1.2%
667
 
0.9%
747
 
0.6%
943
 
0.6%
Other values (299)832
 
11.1%

Length

2022-11-06T21:08:03.717787image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
0460
 
6.2%
1274
 
3.7%
2172
 
2.3%
3138
 
1.8%
496
 
1.3%
588
 
1.2%
667
 
0.9%
747
 
0.6%
943
 
0.6%
Other values (299)832
 
11.1%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p18ym_pb_m
Categorical

HIGH CARDINALITY

Distinct236
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size423.9 KiB
*
5250 
0
631 
1
 
324
2
 
207
3
 
129
Other values (231)
926 

Length

Max length6
Median length1
Mean length1.114503817
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique142 ?
Unique (%)1.9%

Sample

1st row358674
2nd row712
3rd row721
4th row151
5th row121

Common Values

ValueCountFrequency (%)
*5250
70.3%
0631
 
8.5%
1324
 
4.3%
2207
 
2.8%
3129
 
1.7%
487
 
1.2%
553
 
0.7%
845
 
0.6%
643
 
0.6%
739
 
0.5%
Other values (226)659
 
8.8%

Length

2022-11-06T21:08:03.910797image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
0631
 
8.5%
1324
 
4.3%
2207
 
2.8%
3129
 
1.7%
487
 
1.2%
553
 
0.7%
845
 
0.6%
643
 
0.6%
739
 
0.5%
Other values (226)659
 
8.8%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p18ym_pb_f
Categorical

HIGH CARDINALITY

Distinct226
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size423.9 KiB
*
5250 
0
697 
1
 
332
2
 
168
3
 
131
Other values (221)
889 

Length

Max length6
Median length1
Mean length1.110753984
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique134 ?
Unique (%)1.8%

Sample

1st row363413
2nd row520
3rd row321
4th row240
5th row162

Common Values

ValueCountFrequency (%)
*5250
70.3%
0697
 
9.3%
1332
 
4.4%
2168
 
2.2%
3131
 
1.8%
487
 
1.2%
554
 
0.7%
643
 
0.6%
735
 
0.5%
933
 
0.4%
Other values (216)637
 
8.5%

Length

2022-11-06T21:08:04.074787image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
0697
 
9.3%
1332
 
4.4%
2168
 
2.2%
3131
 
1.8%
487
 
1.2%
554
 
0.7%
643
 
0.6%
735
 
0.5%
933
 
0.4%
Other values (216)637
 
8.5%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

graproes
Categorical

HIGH CARDINALITY

Distinct634
Distinct (%)8.5%
Missing0
Missing (%)0.0%
Memory size428.6 KiB
*
5376 
6
 
28
7
 
26
5
 
22
4
 
17
Other values (629)
1998 

Length

Max length5
Median length1
Mean length1.75826972
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique202 ?
Unique (%)2.7%

Sample

1st row9.42
2nd row*
3rd row*
4th row7.81
5th row8.14

Common Values

ValueCountFrequency (%)
*5376
72.0%
628
 
0.4%
726
 
0.3%
522
 
0.3%
417
 
0.2%
5.516
 
0.2%
6.8314
 
0.2%
5.213
 
0.2%
913
 
0.2%
4.7513
 
0.2%
Other values (624)1929
 
25.8%

Length

2022-11-06T21:08:04.292787image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5376
72.0%
628
 
0.4%
726
 
0.3%
522
 
0.3%
417
 
0.2%
5.516
 
0.2%
6.8314
 
0.2%
5.213
 
0.2%
913
 
0.2%
4.7513
 
0.2%
Other values (624)1929
 
25.8%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

graproes_m
Categorical

HIGH CARDINALITY

Distinct599
Distinct (%)8.0%
Missing0
Missing (%)0.0%
Memory size428.3 KiB
*
5376 
6
 
44
5
 
33
9
 
27
7
 
26
Other values (594)
1961 

Length

Max length5
Median length1
Mean length1.712468193
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique210 ?
Unique (%)2.8%

Sample

1st row9.39
2nd row*
3rd row*
4th row7.36
5th row7.7

Common Values

ValueCountFrequency (%)
*5376
72.0%
644
 
0.6%
533
 
0.4%
927
 
0.4%
726
 
0.3%
826
 
0.3%
422
 
0.3%
6.517
 
0.2%
5.3317
 
0.2%
7.517
 
0.2%
Other values (589)1862
 
24.9%

Length

2022-11-06T21:08:04.507790image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5376
72.0%
644
 
0.6%
533
 
0.4%
927
 
0.4%
726
 
0.3%
826
 
0.3%
422
 
0.3%
7.517
 
0.2%
6.6717
 
0.2%
5.3317
 
0.2%
Other values (589)1862
 
24.9%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

graproes_f
Categorical

HIGH CARDINALITY

Distinct577
Distinct (%)7.7%
Missing0
Missing (%)0.0%
Memory size427.9 KiB
*
5376 
6
 
71
7
 
45
5
 
40
8
 
39
Other values (572)
1896 

Length

Max length5
Median length1
Mean length1.666666667
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique208 ?
Unique (%)2.8%

Sample

1st row9.44
2nd row*
3rd row*
4th row8.31
5th row8.64

Common Values

ValueCountFrequency (%)
*5376
72.0%
671
 
1.0%
745
 
0.6%
540
 
0.5%
839
 
0.5%
936
 
0.5%
030
 
0.4%
427
 
0.4%
6.525
 
0.3%
7.525
 
0.3%
Other values (567)1753
 
23.5%

Length

2022-11-06T21:08:04.684789image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5376
72.0%
671
 
1.0%
745
 
0.6%
540
 
0.5%
839
 
0.5%
936
 
0.5%
030
 
0.4%
427
 
0.4%
6.525
 
0.3%
7.525
 
0.3%
Other values (567)1753
 
23.5%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

pea
Categorical

HIGH CARDINALITY

Distinct464
Distinct (%)6.2%
Missing0
Missing (%)0.0%
Memory size425.1 KiB
*
5250 
3
 
148
5
 
141
4
 
137
6
 
110
Other values (459)
1681 

Length

Max length7
Median length1
Mean length1.279228606
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique259 ?
Unique (%)3.5%

Sample

1st row1104922
2nd row5976
3rd row5368
4th row967
5th row641

Common Values

ValueCountFrequency (%)
*5250
70.3%
3148
 
2.0%
5141
 
1.9%
4137
 
1.8%
6110
 
1.5%
780
 
1.1%
861
 
0.8%
952
 
0.7%
252
 
0.7%
1151
 
0.7%
Other values (454)1385
 
18.5%

Length

2022-11-06T21:08:04.855787image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
3148
 
2.0%
5141
 
1.9%
4137
 
1.8%
6110
 
1.5%
780
 
1.1%
861
 
0.8%
952
 
0.7%
252
 
0.7%
1151
 
0.7%
Other values (454)1385
 
18.5%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

pea_m
Categorical

HIGH CARDINALITY

Distinct425
Distinct (%)5.7%
Missing0
Missing (%)0.0%
Memory size424.9 KiB
*
5250 
3
 
207
4
 
154
5
 
149
6
 
84
Other values (420)
1623 

Length

Max length6
Median length1
Mean length1.254319004
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique245 ?
Unique (%)3.3%

Sample

1st row731681
2nd row5315
3rd row4918
4th row746
5th row493

Common Values

ValueCountFrequency (%)
*5250
70.3%
3207
 
2.8%
4154
 
2.1%
5149
 
2.0%
684
 
1.1%
781
 
1.1%
274
 
1.0%
862
 
0.8%
950
 
0.7%
1048
 
0.6%
Other values (415)1308
 
17.5%

Length

2022-11-06T21:08:05.029791image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
3207
 
2.8%
4154
 
2.1%
5149
 
2.0%
684
 
1.1%
781
 
1.1%
274
 
1.0%
862
 
0.8%
950
 
0.7%
1048
 
0.6%
Other values (415)1308
 
17.5%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

pea_f
Categorical

HIGH CARDINALITY

Distinct256
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size424.0 KiB
*
5250 
0
533 
1
 
315
2
 
201
3
 
134
Other values (251)
1034 

Length

Max length6
Median length1
Mean length1.128833534
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique155 ?
Unique (%)2.1%

Sample

1st row373241
2nd row661
3rd row450
4th row221
5th row148

Common Values

ValueCountFrequency (%)
*5250
70.3%
0533
 
7.1%
1315
 
4.2%
2201
 
2.7%
3134
 
1.8%
572
 
1.0%
469
 
0.9%
656
 
0.7%
746
 
0.6%
844
 
0.6%
Other values (246)747
 
10.0%

Length

2022-11-06T21:08:05.198789image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
0533
 
7.1%
1315
 
4.2%
2201
 
2.7%
3134
 
1.8%
572
 
1.0%
469
 
0.9%
656
 
0.7%
746
 
0.6%
844
 
0.6%
Other values (246)747
 
10.0%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

pe_inac
Categorical

HIGH CARDINALITY

Distinct481
Distinct (%)6.4%
Missing0
Missing (%)0.0%
Memory size425.0 KiB
*
5250 
4
 
141
3
 
131
6
 
112
5
 
103
Other values (476)
1730 

Length

Max length6
Median length1
Mean length1.266372037
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique287 ?
Unique (%)3.8%

Sample

1st row911919
2nd row4304
3rd row2448
4th row1074
5th row720

Common Values

ValueCountFrequency (%)
*5250
70.3%
4141
 
1.9%
3131
 
1.8%
6112
 
1.5%
5103
 
1.4%
295
 
1.3%
787
 
1.2%
179
 
1.1%
878
 
1.0%
955
 
0.7%
Other values (471)1336
 
17.9%

Length

2022-11-06T21:08:05.370787image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
4141
 
1.9%
3131
 
1.8%
6112
 
1.5%
5103
 
1.4%
295
 
1.3%
787
 
1.2%
179
 
1.1%
878
 
1.0%
955
 
0.7%
Other values (471)1336
 
17.9%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

pe_inac_m
Categorical

HIGH CARDINALITY

Distinct288
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Memory size424.2 KiB
*
5250 
0
 
389
1
 
298
2
 
226
3
 
143
Other values (283)
1161 

Length

Max length6
Median length1
Mean length1.153073524
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique170 ?
Unique (%)2.3%

Sample

1st row277494
2nd row1011
3rd row985
4th row324
5th row236

Common Values

ValueCountFrequency (%)
*5250
70.3%
0389
 
5.2%
1298
 
4.0%
2226
 
3.0%
3143
 
1.9%
488
 
1.2%
569
 
0.9%
657
 
0.8%
747
 
0.6%
833
 
0.4%
Other values (278)867
 
11.6%

Length

2022-11-06T21:08:05.529787image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
0389
 
5.2%
1298
 
4.0%
2226
 
3.0%
3143
 
1.9%
488
 
1.2%
569
 
0.9%
657
 
0.8%
747
 
0.6%
833
 
0.4%
Other values (278)867
 
11.6%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

pe_inac_f
Categorical

HIGH CARDINALITY

Distinct415
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Memory size424.8 KiB
*
5250 
3
 
189
2
 
147
5
 
140
4
 
135
Other values (410)
1606 

Length

Max length6
Median length1
Mean length1.236239454
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique234 ?
Unique (%)3.1%

Sample

1st row634425
2nd row3293
3rd row1463
4th row750
5th row484

Common Values

ValueCountFrequency (%)
*5250
70.3%
3189
 
2.5%
2147
 
2.0%
5140
 
1.9%
4135
 
1.8%
1104
 
1.4%
687
 
1.2%
768
 
0.9%
865
 
0.9%
943
 
0.6%
Other values (405)1239
 
16.6%

Length

2022-11-06T21:08:05.683790image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
3189
 
2.5%
2147
 
2.0%
5140
 
1.9%
4135
 
1.8%
1104
 
1.4%
687
 
1.2%
768
 
0.9%
865
 
0.9%
043
 
0.6%
Other values (405)1239
 
16.6%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

pocupada
Categorical

HIGH CARDINALITY

Distinct470
Distinct (%)6.3%
Missing0
Missing (%)0.0%
Memory size425.1 KiB
*
5250 
3
 
152
4
 
147
5
 
128
6
 
107
Other values (465)
1683 

Length

Max length7
Median length1
Mean length1.27373778
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique285 ?
Unique (%)3.8%

Sample

1st row1043459
2nd row5853
3rd row5204
4th row892
5th row575

Common Values

ValueCountFrequency (%)
*5250
70.3%
3152
 
2.0%
4147
 
2.0%
5128
 
1.7%
6107
 
1.4%
782
 
1.1%
264
 
0.9%
858
 
0.8%
1051
 
0.7%
949
 
0.7%
Other values (460)1379
 
18.5%

Length

2022-11-06T21:08:05.841786image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
3152
 
2.0%
4147
 
2.0%
5128
 
1.7%
6107
 
1.4%
782
 
1.1%
264
 
0.9%
858
 
0.8%
1051
 
0.7%
949
 
0.7%
Other values (460)1379
 
18.5%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

pocupada_m
Categorical

HIGH CARDINALITY

Distinct406
Distinct (%)5.4%
Missing0
Missing (%)0.0%
Memory size424.9 KiB
*
5250 
3
 
213
4
 
155
5
 
135
2
 
91
Other values (401)
1623 

Length

Max length6
Median length1
Mean length1.24842641
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique230 ?
Unique (%)3.1%

Sample

1st row684552
2nd row5210
3rd row4763
4th row679
5th row433

Common Values

ValueCountFrequency (%)
*5250
70.3%
3213
 
2.9%
4155
 
2.1%
5135
 
1.8%
291
 
1.2%
686
 
1.2%
779
 
1.1%
961
 
0.8%
858
 
0.8%
1144
 
0.6%
Other values (396)1295
 
17.3%

Length

2022-11-06T21:08:06.066792image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
3213
 
2.9%
4155
 
2.1%
5135
 
1.8%
291
 
1.2%
686
 
1.2%
779
 
1.1%
961
 
0.8%
858
 
0.8%
1144
 
0.6%
Other values (396)1295
 
17.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

pocupada_f
Categorical

HIGH CARDINALITY

Distinct257
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size424.0 KiB
*
5250 
0
543 
1
 
317
2
 
208
3
 
128
Other values (252)
1021 

Length

Max length6
Median length1
Mean length1.12655685
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique158 ?
Unique (%)2.1%

Sample

1st row358907
2nd row643
3rd row441
4th row213
5th row142

Common Values

ValueCountFrequency (%)
*5250
70.3%
0543
 
7.3%
1317
 
4.2%
2208
 
2.8%
3128
 
1.7%
569
 
0.9%
469
 
0.9%
660
 
0.8%
745
 
0.6%
843
 
0.6%
Other values (247)735
 
9.8%

Length

2022-11-06T21:08:06.266791image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
0543
 
7.3%
1317
 
4.2%
2208
 
2.8%
3128
 
1.7%
569
 
0.9%
469
 
0.9%
660
 
0.8%
745
 
0.6%
843
 
0.6%
Other values (247)735
 
9.8%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

pdesocup
Categorical

HIGH CARDINALITY

Distinct151
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size423.5 KiB
*
5250 
0
1157 
1
 
279
2
 
128
3
 
79
Other values (146)
574 

Length

Max length5
Median length1
Mean length1.061068702
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique84 ?
Unique (%)1.1%

Sample

1st row61463
2nd row123
3rd row164
4th row75
5th row66

Common Values

ValueCountFrequency (%)
*5250
70.3%
01157
 
15.5%
1279
 
3.7%
2128
 
1.7%
379
 
1.1%
457
 
0.8%
549
 
0.7%
837
 
0.5%
636
 
0.5%
727
 
0.4%
Other values (141)368
 
4.9%

Length

2022-11-06T21:08:06.598787image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
01157
 
15.5%
1279
 
3.7%
2128
 
1.7%
379
 
1.1%
457
 
0.8%
549
 
0.7%
837
 
0.5%
636
 
0.5%
727
 
0.4%
Other values (141)368
 
4.9%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

pdesocup_m
Categorical

HIGH CARDINALITY

Distinct142
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size423.5 KiB
*
5250 
0
1206 
1
 
265
2
 
132
3
 
70
Other values (137)
544 

Length

Max length5
Median length1
Mean length1.054506495
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique77 ?
Unique (%)1.0%

Sample

1st row47129
2nd row105
3rd row155
4th row67
5th row60

Common Values

ValueCountFrequency (%)
*5250
70.3%
01206
 
16.2%
1265
 
3.5%
2132
 
1.8%
370
 
0.9%
469
 
0.9%
541
 
0.5%
838
 
0.5%
632
 
0.4%
728
 
0.4%
Other values (132)336
 
4.5%

Length

2022-11-06T21:08:06.788790image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
01206
 
16.2%
1265
 
3.5%
2132
 
1.8%
370
 
0.9%
469
 
0.9%
541
 
0.5%
838
 
0.5%
632
 
0.4%
728
 
0.4%
Other values (132)336
 
4.5%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

pdesocup_f
Categorical

HIGH CARDINALITY
HIGH CORRELATION
HIGH CORRELATION

Distinct73
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size423.2 KiB
*
5250 
0
1688 
1
 
214
2
 
76
3
 
40
Other values (68)
 
199

Length

Max length5
Median length1
Mean length1.017811705
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique43 ?
Unique (%)0.6%

Sample

1st row14334
2nd row18
3rd row9
4th row8
5th row6

Common Values

ValueCountFrequency (%)
*5250
70.3%
01688
 
22.6%
1214
 
2.9%
276
 
1.0%
340
 
0.5%
431
 
0.4%
526
 
0.3%
621
 
0.3%
810
 
0.1%
79
 
0.1%
Other values (63)102
 
1.4%

Length

2022-11-06T21:08:06.978791image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
01688
 
22.6%
1214
 
2.9%
276
 
1.0%
340
 
0.5%
431
 
0.4%
526
 
0.3%
621
 
0.3%
810
 
0.1%
79
 
0.1%
Other values (63)102
 
1.4%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

psinder
Categorical

HIGH CARDINALITY

Distinct401
Distinct (%)5.4%
Missing0
Missing (%)0.0%
Memory size424.8 KiB
*
5250 
0
 
167
1
 
118
2
 
115
4
 
98
Other values (396)
1719 

Length

Max length6
Median length1
Mean length1.244542654
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique222 ?
Unique (%)3.0%

Sample

1st row666374
2nd row4700
3rd row5005
4th row538
5th row359

Common Values

ValueCountFrequency (%)
*5250
70.3%
0167
 
2.2%
1118
 
1.6%
2115
 
1.5%
498
 
1.3%
393
 
1.2%
690
 
1.2%
577
 
1.0%
762
 
0.8%
952
 
0.7%
Other values (391)1345
 
18.0%

Length

2022-11-06T21:08:07.171789image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
0167
 
2.2%
1118
 
1.6%
2115
 
1.5%
498
 
1.3%
393
 
1.2%
690
 
1.2%
577
 
1.0%
762
 
0.8%
852
 
0.7%
Other values (391)1345
 
18.0%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

pder_ss
Categorical

HIGH CARDINALITY

Distinct613
Distinct (%)8.2%
Missing0
Missing (%)0.0%
Memory size425.6 KiB
*
5250 
6
 
69
5
 
65
8
 
64
9
 
62
Other values (608)
1957 

Length

Max length7
Median length1
Mean length1.351814651
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique376 ?
Unique (%)5.0%

Sample

1st row1970349
2nd row7767
3rd row3958
4th row2096
5th row1381

Common Values

ValueCountFrequency (%)
*5250
70.3%
669
 
0.9%
565
 
0.9%
864
 
0.9%
962
 
0.8%
1060
 
0.8%
757
 
0.8%
354
 
0.7%
1154
 
0.7%
451
 
0.7%
Other values (603)1681
 
22.5%

Length

2022-11-06T21:08:07.350791image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
669
 
0.9%
565
 
0.9%
864
 
0.9%
962
 
0.8%
1060
 
0.8%
757
 
0.8%
354
 
0.7%
1154
 
0.7%
451
 
0.7%
Other values (603)1681
 
22.5%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

pder_imss
Categorical

HIGH CARDINALITY

Distinct375
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size424.7 KiB
*
5250 
0
 
270
2
 
123
1
 
117
5
 
87
Other values (370)
1620 

Length

Max length7
Median length1
Mean length1.224722111
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique224 ?
Unique (%)3.0%

Sample

1st row1183161
2nd row4673
3rd row2466
4th row528
5th row354

Common Values

ValueCountFrequency (%)
*5250
70.3%
0270
 
3.6%
2123
 
1.6%
1117
 
1.6%
587
 
1.2%
382
 
1.1%
481
 
1.1%
774
 
1.0%
670
 
0.9%
969
 
0.9%
Other values (365)1244
 
16.7%

Length

2022-11-06T21:08:07.517787image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
0270
 
3.6%
2123
 
1.6%
1117
 
1.6%
587
 
1.2%
382
 
1.1%
481
 
1.1%
774
 
1.0%
670
 
0.9%
969
 
0.9%
Other values (365)1244
 
16.7%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

pder_iste
Categorical

HIGH CARDINALITY

Distinct176
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size423.6 KiB
*
5250 
0
1311 
1
 
138
2
 
97
4
 
52
Other values (171)
619 

Length

Max length6
Median length1
Mean length1.073255658
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique106 ?
Unique (%)1.4%

Sample

1st row143663
2nd row144
3rd row90
4th row75
5th row51

Common Values

ValueCountFrequency (%)
*5250
70.3%
01311
 
17.6%
1138
 
1.8%
297
 
1.3%
452
 
0.7%
352
 
0.7%
551
 
0.7%
641
 
0.5%
732
 
0.4%
1027
 
0.4%
Other values (166)416
 
5.6%

Length

2022-11-06T21:08:07.675786image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
01311
 
17.6%
1138
 
1.8%
297
 
1.3%
452
 
0.7%
352
 
0.7%
551
 
0.7%
641
 
0.5%
732
 
0.4%
1027
 
0.4%
Other values (166)416
 
5.6%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

pder_istee
Categorical

HIGH CARDINALITY

Distinct189
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size423.5 KiB
*
5250 
0
1517 
1
 
95
2
 
78
3
 
45
Other values (184)
 
482

Length

Max length6
Median length1
Mean length1.064684612
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique124 ?
Unique (%)1.7%

Sample

1st row128563
2nd row123
3rd row25
4th row212
5th row194

Common Values

ValueCountFrequency (%)
*5250
70.3%
01517
 
20.3%
195
 
1.3%
278
 
1.0%
345
 
0.6%
440
 
0.5%
538
 
0.5%
925
 
0.3%
625
 
0.3%
716
 
0.2%
Other values (179)338
 
4.5%

Length

2022-11-06T21:08:07.846791image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
01517
 
20.3%
195
 
1.3%
278
 
1.0%
345
 
0.6%
440
 
0.5%
538
 
0.5%
925
 
0.3%
625
 
0.3%
716
 
0.2%
Other values (179)338
 
4.5%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

pder_segp
Categorical

HIGH CARDINALITY

Distinct485
Distinct (%)6.5%
Missing0
Missing (%)0.0%
Memory size424.9 KiB
*
5250 
0
 
393
1
 
104
2
 
93
3
 
83
Other values (480)
1544 

Length

Max length6
Median length1
Mean length1.258068836
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique283 ?
Unique (%)3.8%

Sample

1st row460109
2nd row2640
3rd row1283
4th row1275
5th row778

Common Values

ValueCountFrequency (%)
*5250
70.3%
0393
 
5.3%
1104
 
1.4%
293
 
1.2%
383
 
1.1%
482
 
1.1%
578
 
1.0%
746
 
0.6%
936
 
0.5%
636
 
0.5%
Other values (475)1266
 
17.0%

Length

2022-11-06T21:08:08.009813image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
0393
 
5.3%
1104
 
1.4%
293
 
1.2%
383
 
1.1%
482
 
1.1%
578
 
1.0%
746
 
0.6%
936
 
0.5%
636
 
0.5%
Other values (475)1266
 
17.0%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p12ym_solt
Categorical

HIGH CARDINALITY

Distinct397
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Memory size424.7 KiB
*
5250 
2
 
178
3
 
159
1
 
148
4
 
126
Other values (392)
1606 

Length

Max length6
Median length1
Mean length1.228070175
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique232 ?
Unique (%)3.1%

Sample

1st row701078
2nd row3078
3rd row2940
4th row678
5th row471

Common Values

ValueCountFrequency (%)
*5250
70.3%
2178
 
2.4%
3159
 
2.1%
1148
 
2.0%
4126
 
1.7%
5101
 
1.4%
099
 
1.3%
686
 
1.2%
757
 
0.8%
847
 
0.6%
Other values (387)1216
 
16.3%

Length

2022-11-06T21:08:08.174790image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
2178
 
2.4%
3159
 
2.1%
1148
 
2.0%
4126
 
1.7%
5101
 
1.4%
099
 
1.3%
686
 
1.2%
757
 
0.8%
847
 
0.6%
Other values (387)1216
 
16.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p12ym_casa
Categorical

HIGH CARDINALITY

Distinct505
Distinct (%)6.8%
Missing0
Missing (%)0.0%
Memory size425.2 KiB
*
5250 
6
 
206
4
 
136
8
 
109
10
 
88
Other values (500)
1678 

Length

Max length7
Median length1
Mean length1.298111691
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique298 ?
Unique (%)4.0%

Sample

1st row1104090
2nd row6049
3rd row4218
4th row1233
5th row794

Common Values

ValueCountFrequency (%)
*5250
70.3%
6206
 
2.8%
4136
 
1.8%
8109
 
1.5%
1088
 
1.2%
281
 
1.1%
1260
 
0.8%
544
 
0.6%
743
 
0.6%
1443
 
0.6%
Other values (495)1407
 
18.8%

Length

2022-11-06T21:08:08.357787image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
6206
 
2.8%
4136
 
1.8%
8109
 
1.5%
1088
 
1.2%
281
 
1.1%
1260
 
0.8%
544
 
0.6%
743
 
0.6%
1443
 
0.6%
Other values (495)1407
 
18.8%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

p12ym_sepa
Categorical

HIGH CARDINALITY

Distinct244
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size424.0 KiB
*
5250 
0
 
381
1
 
368
2
 
234
3
 
135
Other values (239)
1099 

Length

Max length6
Median length1
Mean length1.133386902
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique144 ?
Unique (%)1.9%

Sample

1st row215898
2nd row1196
3rd row676
4th row144
5th row102

Common Values

ValueCountFrequency (%)
*5250
70.3%
0381
 
5.1%
1368
 
4.9%
2234
 
3.1%
3135
 
1.8%
482
 
1.1%
563
 
0.8%
760
 
0.8%
655
 
0.7%
848
 
0.6%
Other values (234)791
 
10.6%

Length

2022-11-06T21:08:08.526791image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
0381
 
5.1%
1368
 
4.9%
2234
 
3.1%
3135
 
1.8%
482
 
1.1%
563
 
0.8%
760
 
0.8%
655
 
0.7%
848
 
0.6%
Other values (234)791
 
10.6%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

pcatolica
Categorical

HIGH CARDINALITY

Distinct641
Distinct (%)8.6%
Missing0
Missing (%)0.0%
Memory size425.9 KiB
*
5250 
8
 
66
9
 
63
7
 
62
11
 
61
Other values (636)
1965 

Length

Max length7
Median length1
Mean length1.385429222
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique389 ?
Unique (%)5.2%

Sample

1st row2190693
2nd row10570
3rd row7416
4th row2521
5th row1674

Common Values

ValueCountFrequency (%)
*5250
70.3%
866
 
0.9%
963
 
0.8%
762
 
0.8%
1161
 
0.8%
1054
 
0.7%
652
 
0.7%
1647
 
0.6%
1444
 
0.6%
1244
 
0.6%
Other values (631)1724
 
23.1%

Length

2022-11-06T21:08:08.699790image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
866
 
0.9%
963
 
0.8%
762
 
0.8%
1161
 
0.8%
1054
 
0.7%
652
 
0.7%
1647
 
0.6%
1444
 
0.6%
1244
 
0.6%
Other values (631)1724
 
23.1%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

pncatolica
Categorical

HIGH CARDINALITY

Distinct247
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size423.9 KiB
*
5250 
0
963 
1
 
140
2
 
105
3
 
83
Other values (242)
926 

Length

Max length6
Median length1
Mean length1.11932503
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique152 ?
Unique (%)2.0%

Sample

1st row257154
2nd row775
3rd row775
4th row62
5th row41

Common Values

ValueCountFrequency (%)
*5250
70.3%
0963
 
12.9%
1140
 
1.9%
2105
 
1.4%
383
 
1.1%
470
 
0.9%
559
 
0.8%
649
 
0.7%
834
 
0.5%
730
 
0.4%
Other values (237)684
 
9.2%

Length

2022-11-06T21:08:08.899789image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
0963
 
12.9%
1140
 
1.9%
2105
 
1.4%
383
 
1.1%
470
 
0.9%
559
 
0.8%
649
 
0.7%
834
 
0.5%
730
 
0.4%
Other values (237)684
 
9.2%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

potras_rel
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct32
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size423.1 KiB
*
5250 
0
2133 
1
 
24
2
 
14
3
 
7
Other values (27)
 
39

Length

Max length4
Median length1
Mean length1.004955136
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)0.3%

Sample

1st row1663
2nd row2
3rd row3
4th row0
5th row0

Common Values

ValueCountFrequency (%)
*5250
70.3%
02133
28.6%
124
 
0.3%
214
 
0.2%
37
 
0.1%
46
 
0.1%
63
 
< 0.1%
382
 
< 0.1%
142
 
< 0.1%
942
 
< 0.1%
Other values (22)24
 
0.3%

Length

2022-11-06T21:08:09.062788image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
02133
28.6%
124
 
0.3%
214
 
0.2%
37
 
0.1%
46
 
0.1%
63
 
< 0.1%
382
 
< 0.1%
142
 
< 0.1%
942
 
< 0.1%
Other values (22)24
 
0.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

psin_relig
Categorical

HIGH CARDINALITY

Distinct233
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size423.9 KiB
*
5250 
0
887 
1
 
195
2
 
103
3
 
87
Other values (228)
945 

Length

Max length6
Median length1
Mean length1.109950449
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique143 ?
Unique (%)1.9%

Sample

1st row174281
2nd row977
3rd row713
4th row33
5th row20

Common Values

ValueCountFrequency (%)
*5250
70.3%
0887
 
11.9%
1195
 
2.6%
2103
 
1.4%
387
 
1.2%
480
 
1.1%
577
 
1.0%
743
 
0.6%
641
 
0.5%
941
 
0.5%
Other values (223)663
 
8.9%

Length

2022-11-06T21:08:09.239787image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
0887
 
11.9%
1195
 
2.6%
2103
 
1.4%
387
 
1.2%
480
 
1.1%
577
 
1.0%
743
 
0.6%
641
 
0.5%
941
 
0.5%
Other values (223)663
 
8.9%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

tothog
Categorical

HIGH CARDINALITY

Distinct401
Distinct (%)5.4%
Missing0
Missing (%)0.0%
Memory size424.8 KiB
*
5250 
3
 
373
4
 
196
5
 
128
6
 
96
Other values (396)
1424 

Length

Max length6
Median length1
Mean length1.235168073
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique234 ?
Unique (%)3.1%

Sample

1st row705668
2nd row4355
3rd row1689
4th row703
5th row471

Common Values

ValueCountFrequency (%)
*5250
70.3%
3373
 
5.0%
4196
 
2.6%
5128
 
1.7%
696
 
1.3%
760
 
0.8%
958
 
0.8%
853
 
0.7%
1040
 
0.5%
1134
 
0.5%
Other values (391)1179
 
15.8%

Length

2022-11-06T21:08:09.425787image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
3373
 
5.0%
4196
 
2.6%
5128
 
1.7%
696
 
1.3%
760
 
0.8%
958
 
0.8%
853
 
0.7%
1040
 
0.5%
1134
 
0.5%
Other values (391)1179
 
15.8%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

hogjef_m
Categorical

HIGH CARDINALITY

Distinct372
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size424.6 KiB
*
5250 
3
 
322
4
 
183
2
 
144
5
 
114
Other values (367)
1454 

Length

Max length6
Median length1
Mean length1.216686755
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique215 ?
Unique (%)2.9%

Sample

1st row524130
2nd row3967
3rd row1483
4th row612
5th row411

Common Values

ValueCountFrequency (%)
*5250
70.3%
3322
 
4.3%
4183
 
2.5%
2144
 
1.9%
5114
 
1.5%
694
 
1.3%
859
 
0.8%
753
 
0.7%
949
 
0.7%
1134
 
0.5%
Other values (362)1165
 
15.6%

Length

2022-11-06T21:08:09.608788image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
3322
 
4.3%
4183
 
2.5%
2144
 
1.9%
5114
 
1.5%
694
 
1.3%
859
 
0.8%
753
 
0.7%
949
 
0.7%
1134
 
0.5%
Other values (362)1165
 
15.6%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

hogjef_f
Categorical

HIGH CARDINALITY

Distinct211
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size423.8 KiB
*
5250 
0
627 
1
 
368
2
 
179
3
 
112
Other values (206)
931 

Length

Max length6
Median length1
Mean length1.103388242
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique127 ?
Unique (%)1.7%

Sample

1st row181538
2nd row388
3rd row206
4th row91
5th row60

Common Values

ValueCountFrequency (%)
*5250
70.3%
0627
 
8.4%
1368
 
4.9%
2179
 
2.4%
3112
 
1.5%
579
 
1.1%
471
 
1.0%
657
 
0.8%
754
 
0.7%
938
 
0.5%
Other values (201)632
 
8.5%

Length

2022-11-06T21:08:09.783786image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
0627
 
8.4%
1368
 
4.9%
2179
 
2.4%
3112
 
1.5%
579
 
1.1%
471
 
1.0%
657
 
0.8%
754
 
0.7%
938
 
0.5%
Other values (201)632
 
8.5%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

pobhog
Categorical

HIGH CARDINALITY

Distinct688
Distinct (%)9.2%
Missing0
Missing (%)0.0%
Memory size426.1 KiB
*
5250 
10
 
65
11
 
62
13
 
59
8
 
58
Other values (683)
1973 

Length

Max length7
Median length1
Mean length1.41221374
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique443 ?
Unique (%)5.9%

Sample

1st row2620624
2nd row12292
3rd row5340
4th row2637
5th row1741

Common Values

ValueCountFrequency (%)
*5250
70.3%
1065
 
0.9%
1162
 
0.8%
1359
 
0.8%
858
 
0.8%
956
 
0.7%
754
 
0.7%
1246
 
0.6%
1542
 
0.6%
1441
 
0.5%
Other values (678)1734
 
23.2%

Length

2022-11-06T21:08:09.958788image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
1065
 
0.9%
1162
 
0.8%
1359
 
0.8%
858
 
0.8%
956
 
0.7%
754
 
0.7%
1246
 
0.6%
1542
 
0.6%
1441
 
0.5%
Other values (678)1734
 
23.2%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

phogjef_m
Categorical

HIGH CARDINALITY

Distinct637
Distinct (%)8.5%
Missing0
Missing (%)0.0%
Memory size425.9 KiB
*
5250 
8
 
63
10
 
62
7
 
62
11
 
61
Other values (632)
1969 

Length

Max length7
Median length1
Mean length1.385429222
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique387 ?
Unique (%)5.2%

Sample

1st row2017290
2nd row11004
3rd row4646
4th row2356
5th row1564

Common Values

ValueCountFrequency (%)
*5250
70.3%
863
 
0.8%
1062
 
0.8%
762
 
0.8%
1161
 
0.8%
955
 
0.7%
1354
 
0.7%
649
 
0.7%
1444
 
0.6%
443
 
0.6%
Other values (627)1724
 
23.1%

Length

2022-11-06T21:08:10.137790image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
863
 
0.8%
1062
 
0.8%
762
 
0.8%
1161
 
0.8%
955
 
0.7%
1354
 
0.7%
649
 
0.7%
1444
 
0.6%
443
 
0.6%
Other values (627)1724
 
23.1%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

phogjef_f
Categorical

HIGH CARDINALITY

Distinct345
Distinct (%)4.6%
Missing0
Missing (%)0.0%
Memory size424.4 KiB
*
5250 
0
627 
2
 
98
3
 
87
4
 
77
Other values (340)
1328 

Length

Max length6
Median length1
Mean length1.188563011
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique204 ?
Unique (%)2.7%

Sample

1st row603334
2nd row1288
3rd row694
4th row281
5th row177

Common Values

ValueCountFrequency (%)
*5250
70.3%
0627
 
8.4%
298
 
1.3%
387
 
1.2%
477
 
1.0%
172
 
1.0%
668
 
0.9%
561
 
0.8%
751
 
0.7%
847
 
0.6%
Other values (335)1029
 
13.8%

Length

2022-11-06T21:08:10.374787image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
0627
 
8.4%
298
 
1.3%
387
 
1.2%
477
 
1.0%
172
 
1.0%
668
 
0.9%
561
 
0.8%
751
 
0.7%
847
 
0.6%
Other values (335)1029
 
13.8%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

vivtot
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
SKEWED

Distinct447
Distinct (%)6.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean366.6173832
Minimum0
Maximum905662
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size58.5 KiB
2022-11-06T21:08:10.610791image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median2
Q36
95-th percentile153.1
Maximum905662
Range905662
Interquartile range (IQR)5

Descriptive statistics

Standard deviation11660.58648
Coefficient of variation (CV)31.8058745
Kurtosis4936.428612
Mean366.6173832
Median Absolute Deviation (MAD)1
Skewness66.07889289
Sum2737532
Variance135969277
MonotonicityNot monotonic
2022-11-06T21:08:10.877787image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
13201
42.9%
21272
 
17.0%
3562
 
7.5%
4300
 
4.0%
5194
 
2.6%
6153
 
2.0%
795
 
1.3%
883
 
1.1%
973
 
1.0%
1056
 
0.7%
Other values (437)1478
19.8%
ValueCountFrequency (%)
01
 
< 0.1%
13201
42.9%
21272
 
17.0%
3562
 
7.5%
4300
 
4.0%
5194
 
2.6%
6153
 
2.0%
795
 
1.3%
883
 
1.1%
973
 
1.0%
ValueCountFrequency (%)
9056621
< 0.1%
2708231
< 0.1%
2450731
< 0.1%
1420491
< 0.1%
1065861
< 0.1%
725511
< 0.1%
695411
< 0.1%
607571
< 0.1%
538721
< 0.1%
534161
< 0.1%

tvivhab
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
SKEWED

Distinct409
Distinct (%)5.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean287.8558993
Minimum0
Maximum712402
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size58.5 KiB
2022-11-06T21:08:11.096789image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median1
Q33
95-th percentile113
Maximum712402
Range712402
Interquartile range (IQR)2

Descriptive statistics

Standard deviation9188.67366
Coefficient of variation (CV)31.92108858
Kurtosis4904.033184
Mean287.8558993
Median Absolute Deviation (MAD)0
Skewness65.82447851
Sum2149420
Variance84431723.63
MonotonicityNot monotonic
2022-11-06T21:08:11.550792image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
14394
58.8%
2871
 
11.7%
3376
 
5.0%
4202
 
2.7%
5127
 
1.7%
693
 
1.2%
762
 
0.8%
857
 
0.8%
952
 
0.7%
1042
 
0.6%
Other values (399)1191
 
16.0%
ValueCountFrequency (%)
01
 
< 0.1%
14394
58.8%
2871
 
11.7%
3376
 
5.0%
4202
 
2.7%
5127
 
1.7%
693
 
1.2%
762
 
0.8%
857
 
0.8%
952
 
0.7%
ValueCountFrequency (%)
7124021
< 0.1%
2133691
< 0.1%
1969691
< 0.1%
1124261
< 0.1%
833191
< 0.1%
576721
< 0.1%
560421
< 0.1%
478631
< 0.1%
425551
< 0.1%
405881
< 0.1%

tvivpar
Categorical

HIGH CARDINALITY

Distinct446
Distinct (%)6.0%
Missing0
Missing (%)0.0%
Memory size425.1 KiB
*
5250 
3
 
175
4
 
147
6
 
118
5
 
106
Other values (441)
1671 

Length

Max length6
Median length1
Mean length1.281773135
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique259 ?
Unique (%)3.5%

Sample

1st row898928
2nd row7021
3rd row3189
4th row895
5th row617

Common Values

ValueCountFrequency (%)
*5250
70.3%
3175
 
2.3%
4147
 
2.0%
6118
 
1.6%
5106
 
1.4%
772
 
1.0%
864
 
0.9%
955
 
0.7%
1048
 
0.6%
1142
 
0.6%
Other values (436)1390
 
18.6%

Length

2022-11-06T21:08:11.816788image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
3175
 
2.3%
4147
 
2.0%
6118
 
1.6%
5106
 
1.4%
772
 
1.0%
864
 
0.9%
955
 
0.7%
1048
 
0.6%
1142
 
0.6%
Other values (436)1390
 
18.6%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

vivpar_hab
Categorical

HIGH CARDINALITY

Distinct401
Distinct (%)5.4%
Missing0
Missing (%)0.0%
Memory size424.8 KiB
*
5250 
3
 
373
4
 
196
5
 
128
6
 
96
Other values (396)
1424 

Length

Max length6
Median length1
Mean length1.235168073
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique234 ?
Unique (%)3.1%

Sample

1st row705668
2nd row4355
3rd row1689
4th row703
5th row471

Common Values

ValueCountFrequency (%)
*5250
70.3%
3373
 
5.0%
4196
 
2.6%
5128
 
1.7%
696
 
1.3%
760
 
0.8%
958
 
0.8%
853
 
0.7%
1040
 
0.5%
1134
 
0.5%
Other values (391)1179
 
15.8%

Length

2022-11-06T21:08:12.048790image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
3373
 
5.0%
4196
 
2.6%
5128
 
1.7%
696
 
1.3%
760
 
0.8%
958
 
0.8%
853
 
0.7%
1040
 
0.5%
1134
 
0.5%
Other values (391)1179
 
15.8%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

tvivparhab
Categorical

HIGH CARDINALITY

Distinct406
Distinct (%)5.4%
Missing0
Missing (%)0.0%
Memory size424.8 KiB
*
5250 
3
 
371
4
 
201
5
 
128
6
 
90
Other values (401)
1427 

Length

Max length6
Median length1
Mean length1.235837686
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique245 ?
Unique (%)3.3%

Sample

1st row712108
2nd row4383
3rd row1703
4th row703
5th row471

Common Values

ValueCountFrequency (%)
*5250
70.3%
3371
 
5.0%
4201
 
2.7%
5128
 
1.7%
690
 
1.2%
763
 
0.8%
856
 
0.7%
954
 
0.7%
1042
 
0.6%
1135
 
0.5%
Other values (396)1177
 
15.8%

Length

2022-11-06T21:08:12.217793image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
3371
 
5.0%
4201
 
2.7%
5128
 
1.7%
690
 
1.2%
763
 
0.8%
856
 
0.7%
954
 
0.7%
1042
 
0.6%
1135
 
0.5%
Other values (396)1177
 
15.8%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

vivpar_des
Categorical

HIGH CARDINALITY

Distinct195
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size423.8 KiB
*
5250 
0
670 
1
 
289
2
 
157
3
 
123
Other values (190)
978 

Length

Max length6
Median length1
Mean length1.100174099
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique123 ?
Unique (%)1.6%

Sample

1st row140219
2nd row1054
3rd row689
4th row119
5th row86

Common Values

ValueCountFrequency (%)
*5250
70.3%
0670
 
9.0%
1289
 
3.9%
2157
 
2.1%
3123
 
1.6%
495
 
1.3%
587
 
1.2%
670
 
0.9%
749
 
0.7%
946
 
0.6%
Other values (185)631
 
8.5%

Length

2022-11-06T21:08:12.390788image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
0670
 
9.0%
1289
 
3.9%
2157
 
2.1%
3123
 
1.6%
495
 
1.3%
587
 
1.2%
670
 
0.9%
749
 
0.7%
946
 
0.6%
Other values (185)631
 
8.5%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

vivpar_ut
Categorical

HIGH CARDINALITY

Distinct190
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size423.7 KiB
*
5250 
0
787 
1
 
312
2
 
173
3
 
125
Other values (185)
820 

Length

Max length5
Median length1
Mean length1.088522834
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique115 ?
Unique (%)1.5%

Sample

1st row53041
2nd row1612
3rd row811
4th row73
5th row60

Common Values

ValueCountFrequency (%)
*5250
70.3%
0787
 
10.5%
1312
 
4.2%
2173
 
2.3%
3125
 
1.7%
475
 
1.0%
563
 
0.8%
746
 
0.6%
645
 
0.6%
840
 
0.5%
Other values (180)551
 
7.4%

Length

2022-11-06T21:08:12.579787image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
0787
 
10.5%
1312
 
4.2%
2173
 
2.3%
3125
 
1.7%
475
 
1.0%
563
 
0.8%
746
 
0.6%
645
 
0.6%
840
 
0.5%
Other values (180)551
 
7.4%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

ocupvivpar
Categorical

HIGH CARDINALITY

Distinct688
Distinct (%)9.2%
Missing0
Missing (%)0.0%
Memory size426.1 KiB
*
5250 
10
 
65
11
 
62
13
 
59
8
 
58
Other values (683)
1973 

Length

Max length7
Median length1
Mean length1.41221374
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique443 ?
Unique (%)5.9%

Sample

1st row2620624
2nd row12292
3rd row5340
4th row2637
5th row1741

Common Values

ValueCountFrequency (%)
*5250
70.3%
1065
 
0.9%
1162
 
0.8%
1359
 
0.8%
858
 
0.8%
956
 
0.7%
754
 
0.7%
1246
 
0.6%
1542
 
0.6%
1441
 
0.5%
Other values (678)1734
 
23.2%

Length

2022-11-06T21:08:12.753787image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
1065
 
0.9%
1162
 
0.8%
1359
 
0.8%
858
 
0.8%
956
 
0.7%
754
 
0.7%
1246
 
0.6%
1542
 
0.6%
1441
 
0.5%
Other values (678)1734
 
23.2%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

prom_ocup
Categorical

HIGH CARDINALITY

Distinct323
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size428.2 KiB
*
5376 
4
 
76
3
 
76
3.67
 
58
3.33
 
56
Other values (318)
1825 

Length

Max length4
Median length1
Mean length1.701084773
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique88 ?
Unique (%)1.2%

Sample

1st row3.71
2nd row*
3rd row*
4th row3.75
5th row3.7

Common Values

ValueCountFrequency (%)
*5376
72.0%
476
 
1.0%
376
 
1.0%
3.6758
 
0.8%
3.3356
 
0.7%
2.6749
 
0.7%
2.3342
 
0.6%
3.540
 
0.5%
239
 
0.5%
4.3338
 
0.5%
Other values (313)1617
 
21.7%

Length

2022-11-06T21:08:12.918791image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5376
72.0%
476
 
1.0%
376
 
1.0%
3.6758
 
0.8%
3.3356
 
0.7%
2.6749
 
0.7%
2.3342
 
0.6%
3.540
 
0.5%
239
 
0.5%
4.3338
 
0.5%
Other values (313)1617
 
21.7%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

pro_ocup_c
Categorical

HIGH CARDINALITY

Distinct262
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Memory size428.7 KiB
*
5376 
1
 
64
0.75
 
29
1.29
 
29
1.33
 
29
Other values (257)
1940 

Length

Max length4
Median length1
Mean length1.76858176
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique61 ?
Unique (%)0.8%

Sample

1st row0.97
2nd row*
3rd row*
4th row0.96
5th row0.95

Common Values

ValueCountFrequency (%)
*5376
72.0%
164
 
0.9%
0.7529
 
0.4%
1.2929
 
0.4%
1.3329
 
0.4%
1.0828
 
0.4%
1.1727
 
0.4%
227
 
0.4%
0.7726
 
0.3%
0.9225
 
0.3%
Other values (252)1807
 
24.2%

Length

2022-11-06T21:08:13.073787image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5376
72.0%
164
 
0.9%
0.7529
 
0.4%
1.2929
 
0.4%
1.3329
 
0.4%
1.0828
 
0.4%
1.1727
 
0.4%
227
 
0.4%
0.7726
 
0.3%
0.9225
 
0.3%
Other values (252)1807
 
24.2%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

vph_pisodt
Categorical

HIGH CARDINALITY

Distinct394
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Memory size424.6 KiB
*
5250 
3
 
319
4
 
162
2
 
129
5
 
114
Other values (389)
1493 

Length

Max length6
Median length1
Mean length1.216017142
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique243 ?
Unique (%)3.3%

Sample

1st row664291
2nd row3672
3rd row1397
4th row685
5th row457

Common Values

ValueCountFrequency (%)
*5250
70.3%
3319
 
4.3%
4162
 
2.2%
2129
 
1.7%
5114
 
1.5%
681
 
1.1%
068
 
0.9%
760
 
0.8%
859
 
0.8%
154
 
0.7%
Other values (384)1171
 
15.7%

Length

2022-11-06T21:08:13.232790image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
3319
 
4.3%
4162
 
2.2%
2129
 
1.7%
5114
 
1.5%
681
 
1.1%
068
 
0.9%
760
 
0.8%
859
 
0.8%
154
 
0.7%
Other values (384)1171
 
15.7%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

vph_pisoti
Categorical

HIGH CARDINALITY

Distinct139
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size423.6 KiB
*
5250 
0
783 
1
 
293
2
 
172
3
 
150
Other values (134)
819 

Length

Max length5
Median length1
Mean length1.072586045
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique76 ?
Unique (%)1.0%

Sample

1st row37100
2nd row639
3rd row264
4th row15
5th row11

Common Values

ValueCountFrequency (%)
*5250
70.3%
0783
 
10.5%
1293
 
3.9%
2172
 
2.3%
3150
 
2.0%
485
 
1.1%
580
 
1.1%
757
 
0.8%
656
 
0.7%
846
 
0.6%
Other values (129)495
 
6.6%

Length

2022-11-06T21:08:13.421788image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
0783
 
10.5%
1293
 
3.9%
2172
 
2.3%
3150
 
2.0%
485
 
1.1%
580
 
1.1%
757
 
0.8%
656
 
0.7%
846
 
0.6%
Other values (129)495
 
6.6%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

vph_1dor
Categorical

HIGH CARDINALITY

Distinct260
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Memory size424.3 KiB
*
5250 
2
 
264
1
 
254
3
 
213
0
 
111
Other values (255)
1375 

Length

Max length6
Median length1
Mean length1.16579617
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique139 ?
Unique (%)1.9%

Sample

1st row237492
2nd row2053
3rd row830
4th row190
5th row121

Common Values

ValueCountFrequency (%)
*5250
70.3%
2264
 
3.5%
1254
 
3.4%
3213
 
2.9%
0111
 
1.5%
4108
 
1.4%
588
 
1.2%
675
 
1.0%
750
 
0.7%
1046
 
0.6%
Other values (250)1008
 
13.5%

Length

2022-11-06T21:08:13.605801image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
2264
 
3.5%
1254
 
3.4%
3213
 
2.9%
0111
 
1.5%
4108
 
1.4%
588
 
1.2%
675
 
1.0%
750
 
0.7%
1046
 
0.6%
Other values (250)1008
 
13.5%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

vph_2ymasd
Categorical

HIGH CARDINALITY

Distinct321
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size424.4 KiB
*
5250 
2
 
282
1
 
246
3
 
213
0
 
141
Other values (316)
1335 

Length

Max length6
Median length1
Mean length1.177313513
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique188 ?
Unique (%)2.5%

Sample

1st row464441
2nd row2251
3rd row831
4th row511
5th row349

Common Values

ValueCountFrequency (%)
*5250
70.3%
2282
 
3.8%
1246
 
3.3%
3213
 
2.9%
0141
 
1.9%
4112
 
1.5%
591
 
1.2%
662
 
0.8%
744
 
0.6%
1038
 
0.5%
Other values (311)988
 
13.2%

Length

2022-11-06T21:08:13.770790image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
2282
 
3.8%
1246
 
3.3%
3213
 
2.9%
0141
 
1.9%
4112
 
1.5%
591
 
1.2%
662
 
0.8%
744
 
0.6%
1038
 
0.5%
Other values (311)988
 
13.2%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

vph_1cuart
Categorical

HIGH CARDINALITY

Distinct149
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size423.6 KiB
*
5250 
0
696 
1
 
374
2
 
201
3
 
138
Other values (144)
808 

Length

Max length5
Median length1
Mean length1.07593411
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique86 ?
Unique (%)1.2%

Sample

1st row40028
2nd row422
3rd row215
4th row34
5th row23

Common Values

ValueCountFrequency (%)
*5250
70.3%
0696
 
9.3%
1374
 
5.0%
2201
 
2.7%
3138
 
1.8%
4104
 
1.4%
578
 
1.0%
656
 
0.7%
839
 
0.5%
737
 
0.5%
Other values (139)494
 
6.6%

Length

2022-11-06T21:08:13.958788image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
0696
 
9.3%
1374
 
5.0%
2201
 
2.7%
3138
 
1.8%
4104
 
1.4%
578
 
1.0%
656
 
0.7%
839
 
0.5%
737
 
0.5%
Other values (139)494
 
6.6%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

vph_2cuart
Categorical

HIGH CARDINALITY

Distinct204
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size423.9 KiB
*
5250 
0
 
385
1
 
358
2
 
253
3
 
150
Other values (199)
1071 

Length

Max length6
Median length1
Mean length1.116110888
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique120 ?
Unique (%)1.6%

Sample

1st row100314
2nd row1069
3rd row419
4th row107
5th row63

Common Values

ValueCountFrequency (%)
*5250
70.3%
0385
 
5.2%
1358
 
4.8%
2253
 
3.4%
3150
 
2.0%
492
 
1.2%
585
 
1.1%
664
 
0.9%
850
 
0.7%
745
 
0.6%
Other values (194)735
 
9.8%

Length

2022-11-06T21:08:14.153790image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
0385
 
5.2%
1358
 
4.8%
2253
 
3.4%
3150
 
2.0%
492
 
1.2%
585
 
1.1%
664
 
0.9%
850
 
0.7%
745
 
0.6%
Other values (194)735
 
9.8%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

vph_3ymasc
Categorical

HIGH CARDINALITY

Distinct348
Distinct (%)4.7%
Missing0
Missing (%)0.0%
Memory size424.4 KiB
*
5250 
3
 
258
2
 
247
1
 
188
4
 
145
Other values (343)
1379 

Length

Max length6
Median length1
Mean length1.186420249
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique214 ?
Unique (%)2.9%

Sample

1st row560936
2nd row2811
3rd row1023
4th row559
5th row383

Common Values

ValueCountFrequency (%)
*5250
70.3%
3258
 
3.5%
2247
 
3.3%
1188
 
2.5%
4145
 
1.9%
5100
 
1.3%
095
 
1.3%
670
 
0.9%
744
 
0.6%
838
 
0.5%
Other values (338)1032
 
13.8%

Length

2022-11-06T21:08:14.333791image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
3258
 
3.5%
2247
 
3.3%
1188
 
2.5%
4145
 
1.9%
5100
 
1.3%
095
 
1.3%
670
 
0.9%
744
 
0.6%
838
 
0.5%
Other values (338)1032
 
13.8%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

vph_c_elec
Categorical

HIGH CARDINALITY

Distinct397
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Memory size424.7 KiB
*
5250 
3
 
307
4
 
160
5
 
115
0
 
102
Other values (392)
1533 

Length

Max length6
Median length1
Mean length1.22311504
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique236 ?
Unique (%)3.2%

Sample

1st row689120
2nd row2915
3rd row1318
4th row694
5th row465

Common Values

ValueCountFrequency (%)
*5250
70.3%
3307
 
4.1%
4160
 
2.1%
5115
 
1.5%
0102
 
1.4%
685
 
1.1%
281
 
1.1%
764
 
0.9%
851
 
0.7%
950
 
0.7%
Other values (387)1202
 
16.1%

Length

2022-11-06T21:08:14.613788image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
3307
 
4.1%
4160
 
2.1%
5115
 
1.5%
0102
 
1.4%
685
 
1.1%
281
 
1.1%
764
 
0.9%
851
 
0.7%
950
 
0.7%
Other values (387)1202
 
16.1%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

vph_s_elec
Categorical

HIGH CARDINALITY

Distinct108
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size423.4 KiB
*
5250 
0
1079 
1
 
253
2
 
171
3
 
162
Other values (103)
552 

Length

Max length5
Median length1
Mean length1.041649926
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique60 ?
Unique (%)0.8%

Sample

1st row13352
2nd row1387
3rd row343
4th row6
5th row3

Common Values

ValueCountFrequency (%)
*5250
70.3%
01079
 
14.5%
1253
 
3.4%
2171
 
2.3%
3162
 
2.2%
486
 
1.2%
559
 
0.8%
740
 
0.5%
639
 
0.5%
838
 
0.5%
Other values (98)290
 
3.9%

Length

2022-11-06T21:08:14.828789image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
01079
 
14.5%
1253
 
3.4%
2171
 
2.3%
3162
 
2.2%
486
 
1.2%
559
 
0.8%
740
 
0.5%
639
 
0.5%
838
 
0.5%
Other values (98)290
 
3.9%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

vph_aguadv
Categorical

HIGH CARDINALITY

Distinct379
Distinct (%)5.1%
Missing0
Missing (%)0.0%
Memory size424.6 KiB
*
5250 
0
 
320
3
 
205
2
 
116
4
 
116
Other values (374)
1460 

Length

Max length6
Median length1
Mean length1.209856703
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique225 ?
Unique (%)3.0%

Sample

1st row662273
2nd row1894
3rd row902
4th row690
5th row462

Common Values

ValueCountFrequency (%)
*5250
70.3%
0320
 
4.3%
3205
 
2.7%
2116
 
1.6%
4116
 
1.6%
1104
 
1.4%
578
 
1.0%
662
 
0.8%
751
 
0.7%
941
 
0.5%
Other values (369)1124
 
15.1%

Length

2022-11-06T21:08:15.004788image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
0320
 
4.3%
3205
 
2.7%
2116
 
1.6%
4116
 
1.6%
1104
 
1.4%
578
 
1.0%
662
 
0.8%
751
 
0.7%
941
 
0.5%
Other values (369)1124
 
15.1%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

vph_aguafv
Categorical

HIGH CARDINALITY

Distinct142
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size423.6 KiB
*
5250 
0
684 
1
 
267
3
 
244
2
 
204
Other values (137)
818 

Length

Max length5
Median length1
Mean length1.06923798
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique77 ?
Unique (%)1.0%

Sample

1st row39168
2nd row2401
3rd row758
4th row8
5th row4

Common Values

ValueCountFrequency (%)
*5250
70.3%
0684
 
9.2%
1267
 
3.6%
3244
 
3.3%
2204
 
2.7%
4121
 
1.6%
590
 
1.2%
654
 
0.7%
753
 
0.7%
935
 
0.5%
Other values (132)465
 
6.2%

Length

2022-11-06T21:08:15.183791image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
0684
 
9.2%
1267
 
3.6%
3244
 
3.3%
2204
 
2.7%
4121
 
1.6%
590
 
1.2%
654
 
0.7%
753
 
0.7%
935
 
0.5%
Other values (132)465
 
6.2%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

vph_excsa
Categorical

HIGH CARDINALITY

Distinct393
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Memory size424.7 KiB
*
5250 
3
 
316
4
 
137
5
 
127
2
 
118
Other values (388)
1519 

Length

Max length6
Median length1
Mean length1.22057051
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique229 ?
Unique (%)3.1%

Sample

1st row685319
2nd row3509
3rd row1382
4th row679
5th row456

Common Values

ValueCountFrequency (%)
*5250
70.3%
3316
 
4.2%
4137
 
1.8%
5127
 
1.7%
2118
 
1.6%
691
 
1.2%
174
 
1.0%
760
 
0.8%
055
 
0.7%
949
 
0.7%
Other values (383)1190
 
15.9%

Length

2022-11-06T21:08:15.372790image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
3316
 
4.2%
4137
 
1.8%
5127
 
1.7%
2118
 
1.6%
691
 
1.2%
174
 
1.0%
760
 
0.8%
055
 
0.7%
949
 
0.7%
Other values (383)1190
 
15.9%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

vph_drenaj
Categorical

HIGH CARDINALITY

Distinct331
Distinct (%)4.4%
Missing0
Missing (%)0.0%
Memory size424.3 KiB
*
5250 
0
 
306
3
 
278
1
 
186
2
 
160
Other values (326)
1287 

Length

Max length6
Median length1
Mean length1.164323021
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique209 ?
Unique (%)2.8%

Sample

1st row632352
2nd row2693
3rd row1032
4th row670
5th row454

Common Values

ValueCountFrequency (%)
*5250
70.3%
0306
 
4.1%
3278
 
3.7%
1186
 
2.5%
2160
 
2.1%
4138
 
1.8%
5103
 
1.4%
667
 
0.9%
766
 
0.9%
840
 
0.5%
Other values (321)873
 
11.7%

Length

2022-11-06T21:08:15.563788image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
0306
 
4.1%
3278
 
3.7%
1186
 
2.5%
2160
 
2.1%
4138
 
1.8%
5103
 
1.4%
667
 
0.9%
766
 
0.9%
840
 
0.5%
Other values (321)873
 
11.7%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

vph_nodren
Categorical

HIGH CARDINALITY

Distinct235
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size424.0 KiB
*
5250 
0
 
479
1
 
209
3
 
180
2
 
163
Other values (230)
1186 

Length

Max length5
Median length1
Mean length1.135529664
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique114 ?
Unique (%)1.5%

Sample

1st row68127
2nd row1553
3rd row606
4th row15
5th row9

Common Values

ValueCountFrequency (%)
*5250
70.3%
0479
 
6.4%
1209
 
2.8%
3180
 
2.4%
2163
 
2.2%
4114
 
1.5%
574
 
1.0%
755
 
0.7%
655
 
0.7%
847
 
0.6%
Other values (225)841
 
11.3%

Length

2022-11-06T21:08:15.753788image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
0479
 
6.4%
1209
 
2.8%
3180
 
2.4%
2163
 
2.2%
4114
 
1.5%
574
 
1.0%
755
 
0.7%
655
 
0.7%
847
 
0.6%
Other values (225)841
 
11.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

vph_c_serv
Categorical

HIGH CARDINALITY

Distinct320
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size424.2 KiB
*
5250 
0
557 
3
 
190
1
 
175
2
 
155
Other values (315)
1140 

Length

Max length6
Median length1
Mean length1.153743136
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique201 ?
Unique (%)2.7%

Sample

1st row605751
2nd row1300
3rd row681
4th row665
5th row451

Common Values

ValueCountFrequency (%)
*5250
70.3%
0557
 
7.5%
3190
 
2.5%
1175
 
2.3%
2155
 
2.1%
4106
 
1.4%
589
 
1.2%
658
 
0.8%
746
 
0.6%
834
 
0.5%
Other values (310)807
 
10.8%

Length

2022-11-06T21:08:15.968787image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
0557
 
7.5%
3190
 
2.5%
1175
 
2.3%
2155
 
2.1%
4106
 
1.4%
589
 
1.2%
658
 
0.8%
746
 
0.6%
834
 
0.5%
Other values (310)807
 
10.8%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

vph_snbien
Categorical

HIGH CARDINALITY
HIGH CORRELATION
HIGH CORRELATION

Distinct78
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size423.3 KiB
*
5250 
0
1190 
1
 
318
2
 
161
3
 
127
Other values (73)
 
421

Length

Max length4
Median length1
Mean length1.027855899
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique44 ?
Unique (%)0.6%

Sample

1st row7615
2nd row231
3rd row93
4th row6
5th row4

Common Values

ValueCountFrequency (%)
*5250
70.3%
01190
 
15.9%
1318
 
4.3%
2161
 
2.2%
3127
 
1.7%
463
 
0.8%
652
 
0.7%
542
 
0.6%
732
 
0.4%
928
 
0.4%
Other values (68)204
 
2.7%

Length

2022-11-06T21:08:16.141797image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
01190
 
15.9%
1318
 
4.3%
2161
 
2.2%
3127
 
1.7%
463
 
0.8%
652
 
0.7%
542
 
0.6%
732
 
0.4%
928
 
0.4%
Other values (68)204
 
2.7%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

vph_radio
Categorical

HIGH CARDINALITY

Distinct329
Distinct (%)4.4%
Missing0
Missing (%)0.0%
Memory size424.5 KiB
*
5250 
3
 
283
2
 
197
4
 
160
1
 
124
Other values (324)
1453 

Length

Max length6
Median length1
Mean length1.191509308
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique183 ?
Unique (%)2.5%

Sample

1st row548871
2nd row3334
3rd row1208
4th row371
5th row261

Common Values

ValueCountFrequency (%)
*5250
70.3%
3283
 
3.8%
2197
 
2.6%
4160
 
2.1%
1124
 
1.7%
5119
 
1.6%
677
 
1.0%
769
 
0.9%
850
 
0.7%
047
 
0.6%
Other values (319)1091
 
14.6%

Length

2022-11-06T21:08:16.363815image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
3283
 
3.8%
2197
 
2.6%
4160
 
2.1%
1124
 
1.7%
5119
 
1.6%
677
 
1.0%
769
 
0.9%
850
 
0.7%
047
 
0.6%
Other values (319)1091
 
14.6%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

vph_tv
Categorical

HIGH CARDINALITY

Distinct383
Distinct (%)5.1%
Missing0
Missing (%)0.0%
Memory size424.6 KiB
*
5250 
3
 
287
4
 
159
2
 
139
5
 
118
Other values (378)
1514 

Length

Max length6
Median length1
Mean length1.215213607
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique229 ?
Unique (%)3.1%

Sample

1st row672763
2nd row2842
3rd row1233
4th row681
5th row458

Common Values

ValueCountFrequency (%)
*5250
70.3%
3287
 
3.8%
4159
 
2.1%
2139
 
1.9%
5118
 
1.6%
090
 
1.2%
678
 
1.0%
177
 
1.0%
767
 
0.9%
853
 
0.7%
Other values (373)1149
 
15.4%

Length

2022-11-06T21:08:16.731786image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
3287
 
3.8%
4159
 
2.1%
2139
 
1.9%
5118
 
1.6%
090
 
1.2%
678
 
1.0%
177
 
1.0%
767
 
0.9%
853
 
0.7%
Other values (373)1149
 
15.4%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

vph_refri
Categorical

HIGH CARDINALITY

Distinct376
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size424.5 KiB
*
5250 
3
 
266
0
 
183
4
 
149
2
 
145
Other values (371)
1474 

Length

Max length6
Median length1
Mean length1.203562341
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique222 ?
Unique (%)3.0%

Sample

1st row649253
2nd row2417
3rd row1117
4th row657
5th row440

Common Values

ValueCountFrequency (%)
*5250
70.3%
3266
 
3.6%
0183
 
2.5%
4149
 
2.0%
2145
 
1.9%
5107
 
1.4%
693
 
1.2%
168
 
0.9%
763
 
0.8%
845
 
0.6%
Other values (366)1098
 
14.7%

Length

2022-11-06T21:08:16.936788image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
3266
 
3.6%
0183
 
2.5%
4149
 
2.0%
2145
 
1.9%
5107
 
1.4%
693
 
1.2%
168
 
0.9%
763
 
0.8%
845
 
0.6%
Other values (366)1098
 
14.7%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

vph_lavad
Categorical

HIGH CARDINALITY

Distinct312
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size424.2 KiB
*
5250 
0
 
328
2
 
263
1
 
235
3
 
191
Other values (307)
1200 

Length

Max length6
Median length1
Mean length1.159769653
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique191 ?
Unique (%)2.6%

Sample

1st row514339
2nd row1366
3rd row713
4th row523
5th row337

Common Values

ValueCountFrequency (%)
*5250
70.3%
0328
 
4.4%
2263
 
3.5%
1235
 
3.1%
3191
 
2.6%
4112
 
1.5%
586
 
1.2%
661
 
0.8%
742
 
0.6%
842
 
0.6%
Other values (302)857
 
11.5%

Length

2022-11-06T21:08:17.116787image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
0328
 
4.4%
2263
 
3.5%
1235
 
3.1%
3191
 
2.6%
4112
 
1.5%
586
 
1.2%
661
 
0.8%
742
 
0.6%
842
 
0.6%
Other values (302)857
 
11.5%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

vph_autom
Categorical

HIGH CARDINALITY

Distinct295
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size424.2 KiB
*
5250 
2
 
275
1
 
233
3
 
231
0
 
157
Other values (290)
1321 

Length

Max length6
Median length1
Mean length1.162448105
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique173 ?
Unique (%)2.3%

Sample

1st row443427
2nd row2449
3rd row928
4th row435
5th row268

Common Values

ValueCountFrequency (%)
*5250
70.3%
2275
 
3.7%
1233
 
3.1%
3231
 
3.1%
0157
 
2.1%
4122
 
1.6%
5102
 
1.4%
674
 
1.0%
753
 
0.7%
847
 
0.6%
Other values (285)923
 
12.4%

Length

2022-11-06T21:08:17.288786image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
2275
 
3.7%
1233
 
3.1%
3231
 
3.1%
0157
 
2.1%
4122
 
1.6%
5102
 
1.4%
674
 
1.0%
753
 
0.7%
847
 
0.6%
Other values (285)923
 
12.4%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

vph_pc
Categorical

HIGH CARDINALITY

Distinct185
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size423.6 KiB
*
5250 
0
1125 
1
 
315
2
 
142
3
 
78
Other values (180)
557 

Length

Max length6
Median length1
Mean length1.071246819
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique117 ?
Unique (%)1.6%

Sample

1st row267201
2nd row244
3rd row137
4th row153
5th row110

Common Values

ValueCountFrequency (%)
*5250
70.3%
01125
 
15.1%
1315
 
4.2%
2142
 
1.9%
378
 
1.0%
454
 
0.7%
534
 
0.5%
730
 
0.4%
625
 
0.3%
825
 
0.3%
Other values (175)389
 
5.2%

Length

2022-11-06T21:08:17.473787image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
01125
 
15.1%
1315
 
4.2%
2142
 
1.9%
378
 
1.0%
454
 
0.7%
534
 
0.5%
730
 
0.4%
825
 
0.3%
625
 
0.3%
Other values (175)389
 
5.2%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

vph_telef
Categorical

HIGH CARDINALITY

Distinct214
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size423.7 KiB
*
5250 
0
1117 
1
 
325
2
 
133
3
 
73
Other values (209)
569 

Length

Max length6
Median length1
Mean length1.082898085
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique143 ?
Unique (%)1.9%

Sample

1st row300854
2nd row244
3rd row109
4th row266
5th row193

Common Values

ValueCountFrequency (%)
*5250
70.3%
01117
 
15.0%
1325
 
4.4%
2133
 
1.8%
373
 
1.0%
452
 
0.7%
534
 
0.5%
730
 
0.4%
625
 
0.3%
819
 
0.3%
Other values (204)409
 
5.5%

Length

2022-11-06T21:08:17.663788image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
01117
 
15.0%
1325
 
4.4%
2133
 
1.8%
373
 
1.0%
452
 
0.7%
534
 
0.5%
730
 
0.4%
625
 
0.3%
819
 
0.3%
Other values (204)409
 
5.5%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

vph_cel
Categorical

HIGH CARDINALITY

Distinct328
Distinct (%)4.4%
Missing0
Missing (%)0.0%
Memory size424.4 KiB
*
5250 
3
 
282
2
 
205
4
 
165
0
 
134
Other values (323)
1431 

Length

Max length6
Median length1
Mean length1.181465113
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique186 ?
Unique (%)2.5%

Sample

1st row566141
2nd row2830
3rd row1172
4th row393
5th row261

Common Values

ValueCountFrequency (%)
*5250
70.3%
3282
 
3.8%
2205
 
2.7%
4165
 
2.2%
0134
 
1.8%
1119
 
1.6%
5109
 
1.5%
667
 
0.9%
760
 
0.8%
952
 
0.7%
Other values (318)1024
 
13.7%

Length

2022-11-06T21:08:17.847790image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
3282
 
3.8%
2205
 
2.7%
4165
 
2.2%
0134
 
1.8%
1119
 
1.6%
5109
 
1.5%
667
 
0.9%
760
 
0.8%
952
 
0.7%
Other values (318)1024
 
13.7%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

vph_inter
Categorical

HIGH CARDINALITY

Distinct143
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size423.4 KiB
*
5250 
0
1512 
1
 
225
2
 
92
3
 
40
Other values (138)
 
348

Length

Max length6
Median length1
Mean length1.048747824
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique98 ?
Unique (%)1.3%

Sample

1st row204458
2nd row84
3rd row50
4th row91
5th row70

Common Values

ValueCountFrequency (%)
*5250
70.3%
01512
 
20.2%
1225
 
3.0%
292
 
1.2%
340
 
0.5%
432
 
0.4%
523
 
0.3%
619
 
0.3%
917
 
0.2%
1017
 
0.2%
Other values (133)240
 
3.2%

Length

2022-11-06T21:08:18.015792image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5250
70.3%
01512
 
20.2%
1225
 
3.0%
292
 
1.2%
340
 
0.5%
432
 
0.4%
523
 
0.3%
619
 
0.3%
917
 
0.2%
1017
 
0.2%
Other values (133)240
 
3.2%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

tam_loc
Real number (ℝ≥0)

HIGH CORRELATION
MISSING

Distinct13
Distinct (%)0.2%
Missing199
Missing (%)2.7%
Infinite0
Infinite (%)0.0%
Mean1.144193726
Minimum1
Maximum13
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size58.5 KiB
2022-11-06T21:08:18.147790image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile2
Maximum13
Range12
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.7043169267
Coefficient of variation (CV)0.6155574102
Kurtosis75.32512828
Mean1.144193726
Median Absolute Deviation (MAD)0
Skewness7.488844241
Sum8316
Variance0.4960623332
MonotonicityNot monotonic
2022-11-06T21:08:18.323786image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
16803
91.1%
2202
 
2.7%
3112
 
1.5%
487
 
1.2%
526
 
0.3%
618
 
0.2%
75
 
0.1%
95
 
0.1%
114
 
0.1%
103
 
< 0.1%
Other values (3)3
 
< 0.1%
(Missing)199
 
2.7%
ValueCountFrequency (%)
16803
91.1%
2202
 
2.7%
3112
 
1.5%
487
 
1.2%
526
 
0.3%
618
 
0.2%
75
 
0.1%
81
 
< 0.1%
95
 
0.1%
103
 
< 0.1%
ValueCountFrequency (%)
131
 
< 0.1%
121
 
< 0.1%
114
 
0.1%
103
 
< 0.1%
95
 
0.1%
81
 
< 0.1%
75
 
0.1%
618
 
0.2%
526
 
0.3%
487
1.2%

Interactions

2022-11-06T21:07:19.580970image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:07:04.551940image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:07:06.602957image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:07:08.395932image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:07:10.360929image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:07:12.222929image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:07:13.879929image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:07:15.747929image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:07:17.547955image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:07:19.794926image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:07:04.885960image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:07:06.780961image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:07:08.639925image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:07:10.543956image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:07:12.413930image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:07:14.065962image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:07:15.941931image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:07:17.740933image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:07:20.014929image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:07:05.064955image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:07:06.948930image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:07:08.965925image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:07:10.747955image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:07:12.601969image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:07:14.233929image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:07:16.110928image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:07:18.014932image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:07:20.247928image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:07:05.295968image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:07:07.146957image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:07:09.166959image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:07:11.079962image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:07:12.796930image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:07:14.465933image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:07:16.311928image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:07:18.263928image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:07:20.449926image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:07:05.506957image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:07:07.393928image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:07:09.388971image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:07:11.267929image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:07:12.979954image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:07:14.691956image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:07:16.491961image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:07:18.458972image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:07:20.682972image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:07:05.680957image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:07:07.583966image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:07:09.564929image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:07:11.457957image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:07:13.137962image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:07:14.909958image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:07:16.665973image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:07:18.635929image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:07:20.939971image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:07:05.892930image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:07:07.776956image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:07:09.776956image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:07:11.648931image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:07:13.318961image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:07:15.144956image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:07:16.980955image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:07:18.891929image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:07:21.149933image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:07:06.081932image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:07:07.939931image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:07:09.956953image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:07:11.849932image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:07:13.506953image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:07:15.371930image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:07:17.166930image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:07:19.122932image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:07:21.381970image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:07:06.403951image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:07:08.159932image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:07:10.155948image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:07:12.051956image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:07:13.696928image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:07:15.567956image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:07:17.378930image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-11-06T21:07:19.383929image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/

Correlations

2022-11-06T21:08:18.529790image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2022-11-06T21:08:18.928785image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2022-11-06T21:08:19.244813image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2022-11-06T21:08:19.637795image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.
2022-11-06T21:08:20.124787image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Missing values

2022-11-06T21:07:23.859956image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2022-11-06T21:07:28.325022image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.
2022-11-06T21:07:29.578930image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

Sample

First rows

Añoentidadnom_entmunnom_munlocnom_loclongitudlatitudaltitudpobtotpobmaspobfemp_0a2p_0a2_mp_0a2_fp_3ymasp_3ymas_mp_3ymas_fp_5ymasp_5ymas_mp_5ymas_fp_12ymasp_12ymas_mp_12ymas_fp_15ymasp_15ymas_mp_15ymas_fp_18ymasp_18ymas_mp_18ymas_fp_3a5p_3a5_mp_3a5_fp_6a11p_6a11_mp_6a11_fp_8a14p_8a14_mp_8a14_fp_12a14p_12a14_mp_12a14_fp_15a17p_15a17_mp_15a17_fp_18a24p_18a24_mp_18a24_fp_15a49_fp_60ymasp_60ymas_mp_60ymas_frel_h_mpob0_14pob15_64pob65_masprom_hnvpnacentpnacent_mpnacent_fpnacoepnacoe_mpnacoe_fpres2005pres2005_mpres2005_fpresoe05presoe05_mpresoe05_fp3ym_hlip3ym_hli_mp3ym_hli_fp3hlinhep3hlinhe_mp3hlinhe_fp3hli_hep3hli_he_mp3hli_he_fp5_hlip5_hli_nhep5_hli_hephog_indpcon_limpclim_motpclim_vispclim_lengpclim_audpclim_mot2pclim_menpclim_men2psin_limp3a5_noap3a5_noa_mp3a5_noa_fp6a11_noap6a11_noamp6a11_noafp12a14noap12a14noamp12a14noafp15a17ap15a17a_mp15a17a_fp18a24ap18a24a_mp18a24a_fp8a14anp8a14an_mp8a14an_fp15ym_anp15ym_an_mp15ym_an_fp15ym_sep15ym_se_mp15ym_se_fp15pri_inp15pri_inmp15pri_infp15pri_cop15pri_comp15pri_cofp15sec_inp15sec_inmp15sec_infp15sec_cop15sec_comp15sec_cofp18ym_pbp18ym_pb_mp18ym_pb_fgraproesgraproes_mgraproes_fpeapea_mpea_fpe_inacpe_inac_mpe_inac_fpocupadapocupada_mpocupada_fpdesocuppdesocup_mpdesocup_fpsinderpder_sspder_imsspder_istepder_isteepder_segpp12ym_soltp12ym_casap12ym_sepapcatolicapncatolicapotras_relpsin_religtothoghogjef_mhogjef_fpobhogphogjef_mphogjef_fvivtottvivhabtvivparvivpar_habtvivparhabvivpar_desvivpar_utocupvivparprom_ocuppro_ocup_cvph_pisodtvph_pisotivph_1dorvph_2ymasdvph_1cuartvph_2cuartvph_3ymascvph_c_elecvph_s_elecvph_aguadvvph_aguafvvph_excsavph_drenajvph_nodrenvph_c_servvph_snbienvph_radiovph_tvvph_refrivph_lavadvph_automvph_pcvph_telefvph_celvph_intertam_loc
0201026Sonora0Total de la entidad Sonora0Total de la EntidadNaNNaNNaN266248013396121322868146530745727195824956591254876124078323912201201533118968720258231014961101086218743879375999367881722595860242862353155088791977589131474816071815403036333218576117757115143677362740741517927735774435327865167369160496702083232874112175120699101.2776780217159561584312.32175694108908610866084172372149232023142260965112887811320877854542601359446127033738275321419585834552663058624680603101242546261232481198666487236711105361152271246248124002509937835364302140515738840243364854550143531111957559515600610754355228523157757478529725689928751281486952935978335511996421030849655823276611425211851411180562337494684545772261672284107220873586743634139.429.399.441104922731681373241911919277494634425104345968455235890761463471291433466637419703491183161143663128563460109701078110409021589821906932571541663174281705668524130181538262062420172906033349056627124028989287056687121081402195304126206243.710.9766429137100237492464441400281003145609366891201335266227339168685319632352681276057517615548871672763649253514339443427267201300854566141204458NaN
1201026Sonora0Total de la entidad Sonora9998Localidades de una viviendaNaNNaNNaN1259575175078529271258119787206477211578701845601034163663975979260743718925657683488575273302106256749512626925705492922575363062301170639531231625181719799*271580401752*10399618242171951121273910950662243284112601515503342161037499305194544849594287051524355874852781156638917521498603895613427214412816377867854249396113281168781387290819179911992122177158437920517299657641232712520***59765315661430410113293585352106431231051847007767467314412326403078604911961057077529774355396738812292110041288705943937021435543831054161212292**367263920532251422106928112915138718942401350926931553130023133342842241713662449244244283084NaN
2201026Sonora0Total de la entidad Sonora9999Localidades de dos viviendasNaNNaNNaN902665532473304155149867663762300846662692197784759261921755857491809716254881674301155146528295233629370259289177112396261135135310413121267816541275*14226990568*6598459919992251184340873905348204278866312535224710510463282339535010326375428212122394513134885272121101025024263825132241646034529847331815459313146513355158145210603921164813351877744133238119714101042721321***53684918450244898514635204476344116415595005395824669025128329404218676741677537131689148320653404646694321417143189168917036898115340**1397264830831215419102313183439027581382103260668193120812331117713928137109117250NaN
3201026Sonora1Aconchi0Total del MunicipioNaNNaNNaN26371405123212568572508133311752420128211382058108597318969939031755913842139805931116814337021415616292701418061279147132614367204163114.0473716252712.68259113851206189923921263112911011000011010141611004111251571924705834246421310310053475828301614276492773433037022314737419817612769584972812163911512407.817.368.319677462211074324750892679213756785382096528752121275678123314425216203370361291263723562818957038957037031197326373.750.9668515190511341075596946690867967015665637168165752343515326639391NaN
4201026Sonora1Aconchi1Aconchi1101334.0294930.0611.017419338086837311669892777161486175313707386321259670589116562054589484121010610425114410711168439450441729379403244136108115.4747810801792.6617159207951376160585575000011000011010141157532921115111622382216330107373383544222212102372413372215212134782651401258547383371901472831211628.147.78.64641493148720236484575433142666063591381354511947784717941021674410204714116017411564177617471617471471866017413.70.954571112134923633834653462445645494514261458440337268110193261704.0
5201026Sonora1Aconchi2Chavoverachi1101320.0294837.0597.01**********************************************************************************************************************************************************11*********************************1.0
6201026Sonora1Aconchi3La Estancia1101241.0294736.0600.0713372341492524664347317638332306541273268499251248460226234422616814833965937422220392514854144175834637109.09214439602.626933653285236213213001100000000000000321462332767916883123302112993633027189301713120705093484535171812271517918617.136.537.7524819157285762092391845597214257011519184161683413267116011180154267136239021818021818018027117133.961.02176454126938133179117731741674165187176169148128397195213.0
7201026Sonora1Aconchi4Maicobabi1100742.0294808.0752.04**********************************************************************************************************************************************************32*********************************1.0
8201026Sonora1Aconchi6El Rodeo (El Rodeo de Aconchi)1101132.0294552.0580.0261511000261511251411231211231211201191102200000003123307633136.3631852.64261511000251411000000000000000011000000251100000003121100000000005233211106426248.788.678.91111011221011101000101612202715126000871262519898810263.250.5780170088080880802787721401.0
9201026Sonora1Aconchi7San Pablo (San Pablo de Aconchi)1101159.0294620.0576.01457867862137726513168631125557104535199495075218126221111826541189928321715116.424179253.2514578670001306763000000000000000012920110113333000000032142211012756423014161174642271413229136.976.877.0860461452943604614000271174030742975813850238344145132134438443838511453.821.0138011261333380380373703701736362828112901.0

Last rows

Añoentidadnom_entmunnom_munlocnom_loclongitudlatitudaltitudpobtotpobmaspobfemp_0a2p_0a2_mp_0a2_fp_3ymasp_3ymas_mp_3ymas_fp_5ymasp_5ymas_mp_5ymas_fp_12ymasp_12ymas_mp_12ymas_fp_15ymasp_15ymas_mp_15ymas_fp_18ymasp_18ymas_mp_18ymas_fp_3a5p_3a5_mp_3a5_fp_6a11p_6a11_mp_6a11_fp_8a14p_8a14_mp_8a14_fp_12a14p_12a14_mp_12a14_fp_15a17p_15a17_mp_15a17_fp_18a24p_18a24_mp_18a24_fp_15a49_fp_60ymasp_60ymas_mp_60ymas_frel_h_mpob0_14pob15_64pob65_masprom_hnvpnacentpnacent_mpnacent_fpnacoepnacoe_mpnacoe_fpres2005pres2005_mpres2005_fpresoe05presoe05_mpresoe05_fp3ym_hlip3ym_hli_mp3ym_hli_fp3hlinhep3hlinhe_mp3hlinhe_fp3hli_hep3hli_he_mp3hli_he_fp5_hlip5_hli_nhep5_hli_hephog_indpcon_limpclim_motpclim_vispclim_lengpclim_audpclim_mot2pclim_menpclim_men2psin_limp3a5_noap3a5_noa_mp3a5_noa_fp6a11_noap6a11_noamp6a11_noafp12a14noap12a14noamp12a14noafp15a17ap15a17a_mp15a17a_fp18a24ap18a24a_mp18a24a_fp8a14anp8a14an_mp8a14an_fp15ym_anp15ym_an_mp15ym_an_fp15ym_sep15ym_se_mp15ym_se_fp15pri_inp15pri_inmp15pri_infp15pri_cop15pri_comp15pri_cofp15sec_inp15sec_inmp15sec_infp15sec_cop15sec_comp15sec_cofp18ym_pbp18ym_pb_mp18ym_pb_fgraproesgraproes_mgraproes_fpeapea_mpea_fpe_inacpe_inac_mpe_inac_fpocupadapocupada_mpocupada_fpdesocuppdesocup_mpdesocup_fpsinderpder_sspder_imsspder_istepder_isteepder_segpp12ym_soltp12ym_casap12ym_sepapcatolicapncatolicapotras_relpsin_religtothoghogjef_mhogjef_fpobhogphogjef_mphogjef_fvivtottvivhabtvivparvivpar_habtvivparhabvivpar_desvivpar_utocupvivparprom_ocuppro_ocup_cvph_pisodtvph_pisotivph_1dorvph_2ymasdvph_1cuartvph_2cuartvph_3ymascvph_c_elecvph_s_elecvph_aguadvvph_aguafvvph_excsavph_drenajvph_nodrenvph_c_servvph_snbienvph_radiovph_tvvph_refrivph_lavadvph_automvph_pcvph_telefvph_celvph_intertam_loc
7457201026Sonora72San Ignacio Río Muerto264Jorge Stewart II (Bloque 823)1101547.0272350.010.01**********************************************************************************************************************************************************11*********************************1.0
7458201026Sonora72San Ignacio Río Muerto265Melchor Espinoza (Bloque 525)1101540.0272541.014.04**********************************************************************************************************************************************************11*********************************1.0
7459201026Sonora72San Ignacio Río Muerto267Soc. los 14 del Tetabiate1101143.0272745.016.04**********************************************************************************************************************************************************11*********************************1.0
7460201026Sonora72San Ignacio Río Muerto268El Yucateco1101300.0272955.019.03**********************************************************************************************************************************************************11*********************************1.0
7461201026Sonora72San Ignacio Río Muerto269El Tesoro del Sauzal1101331.0272327.010.07340007347347347346330000000000001011013000750701.7562411073400000000000000000000000070000000000001010001101101011101102021016.574.6783304043300003420022413301330770333330072.33121300212103212001321100201.0
7462201026Sonora72San Ignacio Río Muerto272Francisco Ochoa Vasquez1102558.0272148.04.04**********************************************************************************************************************************************************31*********************************1.0
7463201026Sonora72San Ignacio Río Muerto273Campo de Fernando Valenzuela1101858.0272433.09.06**********************************************************************************************************************************************************31*********************************1.0
7464201026Sonora72San Ignacio Río Muerto276Parcela Escolar1101500.0272425.010.014**********************************************************************************************************************************************************22*********************************1.0
7465201026Sonora72San Ignacio Río Muerto9998Localidades de una viviendaNaNNaNNaN2971721251046287168119278164114233142912101298119611581138541182349252423131014140129346664323*8716248*2501461044625212681581108442114700021147210214226139051312719451012118803301101410425205694722391524157832191328199***1049311128488010493110007222514678657213229240190368781629727324968796878745297**6818473913205352331670783749112677148305511660NaN
7466201026Sonora72San Ignacio Río Muerto9999Localidades de dos viviendasNaNNaNNaN80443630377443374423261362554322251302153211561367743321853141174*26459*73393475272413121122000022020236210101174431220110211211000651642127511566331385651***322932862231283110443626001019357637092219380691125222522221280**1391572101015761620101262161813101210150NaN